Overview

Brought to you by YData

Dataset statistics

Number of variables72
Number of observations338887
Missing cells10484744
Missing cells (%)43.0%
Total size in memory186.2 MiB
Average record size in memory576.0 B

Variable types

Text72

Dataset

DescriptionNMNH Material Samples (USNM) 0049394-241126133413365
URLhttps://doi.org/10.15468/jb9tdf

Alerts

institutionID has constant value "http://grbio.org/cool/142r-0w94" Constant
datasetName has constant value "NMNH Material Samples (USNM)" Constant
basisOfRecord has constant value "MaterialSample" Constant
occurrenceStatus has constant value "present" Constant
catalogNumber has 70849 (20.9%) missing values Missing
recordNumber has 182004 (53.7%) missing values Missing
recordedBy has 70286 (20.7%) missing values Missing
individualCount has 39455 (11.6%) missing values Missing
sex has 176768 (52.2%) missing values Missing
lifeStage has 205348 (60.6%) missing values Missing
preparations has 251707 (74.3%) missing values Missing
associatedMedia has 324297 (95.7%) missing values Missing
associatedSequences has 306152 (90.3%) missing values Missing
occurrenceRemarks has 194011 (57.2%) missing values Missing
materialSampleID has 85174 (25.1%) missing values Missing
fieldNumber has 267780 (79.0%) missing values Missing
eventDate has 16375 (4.8%) missing values Missing
startDayOfYear has 18139 (5.4%) missing values Missing
endDayOfYear has 17919 (5.3%) missing values Missing
year has 16375 (4.8%) missing values Missing
month has 17976 (5.3%) missing values Missing
day has 19395 (5.7%) missing values Missing
verbatimEventDate has 236393 (69.8%) missing values Missing
habitat has 302736 (89.3%) missing values Missing
locationID has 285298 (84.2%) missing values Missing
higherGeography has 4532 (1.3%) missing values Missing
continent has 145113 (42.8%) missing values Missing
waterBody has 231871 (68.4%) missing values Missing
islandGroup has 316108 (93.3%) missing values Missing
island has 279899 (82.6%) missing values Missing
country has 14449 (4.3%) missing values Missing
stateProvince has 66313 (19.6%) missing values Missing
county has 140828 (41.6%) missing values Missing
locality has 34120 (10.1%) missing values Missing
minimumElevationInMeters has 249580 (73.6%) missing values Missing
maximumElevationInMeters has 285010 (84.1%) missing values Missing
verbatimElevation has 322925 (95.3%) missing values Missing
minimumDepthInMeters has 264554 (78.1%) missing values Missing
maximumDepthInMeters has 271546 (80.1%) missing values Missing
verbatimDepth has 337405 (99.6%) missing values Missing
decimalLatitude has 73966 (21.8%) missing values Missing
decimalLongitude has 73966 (21.8%) missing values Missing
geodeticDatum has 308701 (91.1%) missing values Missing
coordinateUncertaintyInMeters has 327845 (96.7%) missing values Missing
verbatimLatitude has 230356 (68.0%) missing values Missing
verbatimLongitude has 230383 (68.0%) missing values Missing
verbatimCoordinateSystem has 329806 (97.3%) missing values Missing
georeferenceProtocol has 255857 (75.5%) missing values Missing
georeferenceRemarks has 329359 (97.2%) missing values Missing
identificationQualifier has 333807 (98.5%) missing values Missing
typeStatus has 332270 (98.0%) missing values Missing
identifiedBy has 226576 (66.9%) missing values Missing
scientificName has 24073 (7.1%) missing values Missing
higherClassification has 5896 (1.7%) missing values Missing
kingdom has 10617 (3.1%) missing values Missing
phylum has 36783 (10.9%) missing values Missing
class has 12524 (3.7%) missing values Missing
order has 30456 (9.0%) missing values Missing
family has 18617 (5.5%) missing values Missing
genus has 25842 (7.6%) missing values Missing
subgenus has 336575 (99.3%) missing values Missing
specificEpithet has 33294 (9.8%) missing values Missing
infraspecificEpithet has 327099 (96.5%) missing values Missing
taxonRank has 327114 (96.5%) missing values Missing
scientificNameAuthorship has 174272 (51.4%) missing values Missing
gbifID has unique values Unique
occurrenceID has unique values Unique

Reproduction

Analysis started2025-03-26 20:19:22.440002
Analysis finished2025-03-26 20:19:35.435522
Duration13 seconds
Software versionydata-profiling vv4.12.2
Download configurationconfig.json

Variables

gbifID
Text

Unique 

Distinct338887
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-03-26T16:19:35.686939image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length10
Min length10

Characters and Unicode

Total characters3388870
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique338887 ?
Unique (%)100.0%

Sample

1st row4501677301
2nd row3027962301
3rd row3028050301
4th row3027962302
5th row3028050302
ValueCountFrequency (%)
4501677301 1
 
< 0.1%
3027962302 1
 
< 0.1%
4909491303 1
 
< 0.1%
3041539301 1
 
< 0.1%
3357130301 1
 
< 0.1%
3027962303 1
 
< 0.1%
3758404301 1
 
< 0.1%
3027962304 1
 
< 0.1%
3336913301 1
 
< 0.1%
3028050303 1
 
< 0.1%
Other values (338877) 338877
> 99.9%
2025-03-26T16:19:36.000437image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 542330
16.0%
3 467319
13.8%
9 358153
10.6%
2 357499
10.5%
8 331705
9.8%
4 318022
9.4%
1 298914
8.8%
5 263991
7.8%
7 254771
7.5%
6 196166
 
5.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3388870
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 542330
16.0%
3 467319
13.8%
9 358153
10.6%
2 357499
10.5%
8 331705
9.8%
4 318022
9.4%
1 298914
8.8%
5 263991
7.8%
7 254771
7.5%
6 196166
 
5.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3388870
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 542330
16.0%
3 467319
13.8%
9 358153
10.6%
2 357499
10.5%
8 331705
9.8%
4 318022
9.4%
1 298914
8.8%
5 263991
7.8%
7 254771
7.5%
6 196166
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3388870
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 542330
16.0%
3 467319
13.8%
9 358153
10.6%
2 357499
10.5%
8 331705
9.8%
4 318022
9.4%
1 298914
8.8%
5 263991
7.8%
7 254771
7.5%
6 196166
 
5.8%
Distinct10798
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-03-26T16:19:36.169151image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length19
Median length19
Mean length19
Min length19

Characters and Unicode

Total characters6438853
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2110 ?
Unique (%)0.6%

Sample

1st row2024-06-26 12:37:00
2nd row2021-10-14 09:12:00
3rd row2022-07-20 16:25:00
4th row2021-10-13 15:49:00
5th row2019-06-25 16:21:00
ValueCountFrequency (%)
2021-05-07 25004
 
3.7%
2024-09-05 21522
 
3.2%
2022-10-06 14747
 
2.2%
2021-10-14 13121
 
1.9%
2021-10-13 13021
 
1.9%
2024-01-01 11167
 
1.6%
2024-10-17 10252
 
1.5%
2017-12-07 9804
 
1.4%
2023-12-17 9676
 
1.4%
2022-07-20 9534
 
1.4%
Other values (1817) 539926
79.7%
2025-03-26T16:19:36.408295image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1620363
25.2%
2 1050470
16.3%
1 804538
12.5%
- 677774
10.5%
: 677774
10.5%
338887
 
5.3%
3 230630
 
3.6%
4 214062
 
3.3%
5 202755
 
3.1%
7 196987
 
3.1%
Other values (3) 424613
 
6.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6438853
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 1620363
25.2%
2 1050470
16.3%
1 804538
12.5%
- 677774
10.5%
: 677774
10.5%
338887
 
5.3%
3 230630
 
3.6%
4 214062
 
3.3%
5 202755
 
3.1%
7 196987
 
3.1%
Other values (3) 424613
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6438853
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 1620363
25.2%
2 1050470
16.3%
1 804538
12.5%
- 677774
10.5%
: 677774
10.5%
338887
 
5.3%
3 230630
 
3.6%
4 214062
 
3.3%
5 202755
 
3.1%
7 196987
 
3.1%
Other values (3) 424613
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6438853
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 1620363
25.2%
2 1050470
16.3%
1 804538
12.5%
- 677774
10.5%
: 677774
10.5%
338887
 
5.3%
3 230630
 
3.6%
4 214062
 
3.3%
5 202755
 
3.1%
7 196987
 
3.1%
Other values (3) 424613
 
6.6%

institutionID
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-03-26T16:19:36.457917image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length31
Mean length31
Min length31

Characters and Unicode

Total characters10505497
Distinct characters20
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowhttp://grbio.org/cool/142r-0w94
2nd rowhttp://grbio.org/cool/142r-0w94
3rd rowhttp://grbio.org/cool/142r-0w94
4th rowhttp://grbio.org/cool/142r-0w94
5th rowhttp://grbio.org/cool/142r-0w94
ValueCountFrequency (%)
http://grbio.org/cool/142r-0w94 338887
100.0%
2025-03-26T16:19:36.547822image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 1355548
 
12.9%
o 1355548
 
12.9%
r 1016661
 
9.7%
g 677774
 
6.5%
t 677774
 
6.5%
4 677774
 
6.5%
h 338887
 
3.2%
1 338887
 
3.2%
w 338887
 
3.2%
0 338887
 
3.2%
Other values (10) 3388870
32.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 10505497
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 1355548
 
12.9%
o 1355548
 
12.9%
r 1016661
 
9.7%
g 677774
 
6.5%
t 677774
 
6.5%
4 677774
 
6.5%
h 338887
 
3.2%
1 338887
 
3.2%
w 338887
 
3.2%
0 338887
 
3.2%
Other values (10) 3388870
32.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 10505497
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 1355548
 
12.9%
o 1355548
 
12.9%
r 1016661
 
9.7%
g 677774
 
6.5%
t 677774
 
6.5%
4 677774
 
6.5%
h 338887
 
3.2%
1 338887
 
3.2%
w 338887
 
3.2%
0 338887
 
3.2%
Other values (10) 3388870
32.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 10505497
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 1355548
 
12.9%
o 1355548
 
12.9%
r 1016661
 
9.7%
g 677774
 
6.5%
t 677774
 
6.5%
4 677774
 
6.5%
h 338887
 
3.2%
1 338887
 
3.2%
w 338887
 
3.2%
0 338887
 
3.2%
Other values (10) 3388870
32.3%
Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-03-26T16:19:36.583448image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length45
Median length45
Mean length45
Min length45

Characters and Unicode

Total characters15249915
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowurn:uuid:18e3cd08-a962-4f0a-b72c-9a0b3600c5ad
2nd rowurn:uuid:f14c21a9-8cbf-4c8b-817f-d19d427e2dd6
3rd rowurn:uuid:f14c21a9-8cbf-4c8b-817f-d19d427e2dd6
4th rowurn:uuid:f14c21a9-8cbf-4c8b-817f-d19d427e2dd6
5th rowurn:uuid:60e28f81-e634-4869-aa3e-732caed713c8
ValueCountFrequency (%)
urn:uuid:18e3cd08-a962-4f0a-b72c-9a0b3600c5ad 119295
35.2%
urn:uuid:f14c21a9-8cbf-4c8b-817f-d19d427e2dd6 74537
22.0%
urn:uuid:60e28f81-e634-4869-aa3e-732caed713c8 42351
 
12.5%
urn:uuid:09c9cf5f-f5d3-48cc-b5c8-cd9b9fbd631f 41666
 
12.3%
urn:uuid:cc104cbf-fd8e-4801-9b71-36731a7db1a0 28321
 
8.4%
urn:uuid:59e56a59-8615-4e0c-841d-eb88f3876b22 24541
 
7.2%
urn:uuid:73d83e23-1999-42cd-b38a-c06a7d32d893 8176
 
2.4%
2025-03-26T16:19:36.770404image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1355548
 
8.9%
d 1156861
 
7.6%
c 1042050
 
6.8%
u 1016661
 
6.7%
8 918812
 
6.0%
0 798172
 
5.2%
a 776305
 
5.1%
1 742674
 
4.9%
9 706786
 
4.6%
: 677774
 
4.4%
Other values (12) 6058272
39.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 15249915
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
- 1355548
 
8.9%
d 1156861
 
7.6%
c 1042050
 
6.8%
u 1016661
 
6.7%
8 918812
 
6.0%
0 798172
 
5.2%
a 776305
 
5.1%
1 742674
 
4.9%
9 706786
 
4.6%
: 677774
 
4.4%
Other values (12) 6058272
39.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 15249915
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
- 1355548
 
8.9%
d 1156861
 
7.6%
c 1042050
 
6.8%
u 1016661
 
6.7%
8 918812
 
6.0%
0 798172
 
5.2%
a 776305
 
5.1%
1 742674
 
4.9%
9 706786
 
4.6%
: 677774
 
4.4%
Other values (12) 6058272
39.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 15249915
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
- 1355548
 
8.9%
d 1156861
 
7.6%
c 1042050
 
6.8%
u 1016661
 
6.7%
8 918812
 
6.0%
0 798172
 
5.2%
a 776305
 
5.1%
1 742674
 
4.9%
9 706786
 
4.6%
: 677774
 
4.4%
Other values (12) 6058272
39.7%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-03-26T16:19:36.804212image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length3.750058279
Min length2

Characters and Unicode

Total characters1270846
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUSNM
2nd rowUSNM
3rd rowUSNM
4th rowUSNM
5th rowUS
ValueCountFrequency (%)
usnm 296536
87.5%
us 42351
 
12.5%
2025-03-26T16:19:36.894684image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
U 338887
26.7%
S 338887
26.7%
N 296536
23.3%
M 296536
23.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1270846
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
U 338887
26.7%
S 338887
26.7%
N 296536
23.3%
M 296536
23.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1270846
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
U 338887
26.7%
S 338887
26.7%
N 296536
23.3%
M 296536
23.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1270846
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
U 338887
26.7%
S 338887
26.7%
N 296536
23.3%
M 296536
23.3%
Distinct7
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-03-26T16:19:36.924680image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length5
Median length4
Mean length2.982271377
Min length2

Characters and Unicode

Total characters1010653
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowENT
2nd rowIZ
3rd rowIZ
4th rowIZ
5th rowUS
ValueCountFrequency (%)
ent 119295
35.2%
iz 74537
22.0%
us 42351
 
12.5%
fish 41666
 
12.3%
herp 28321
 
8.4%
mamm 24541
 
7.2%
birds 8176
 
2.4%
2025-03-26T16:19:37.017046image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 147616
14.6%
I 124379
12.3%
N 119295
11.8%
T 119295
11.8%
S 92193
9.1%
Z 74537
7.4%
M 73623
7.3%
H 69987
6.9%
U 42351
 
4.2%
F 41666
 
4.1%
Other values (5) 105711
10.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1010653
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 147616
14.6%
I 124379
12.3%
N 119295
11.8%
T 119295
11.8%
S 92193
9.1%
Z 74537
7.4%
M 73623
7.3%
H 69987
6.9%
U 42351
 
4.2%
F 41666
 
4.1%
Other values (5) 105711
10.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1010653
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 147616
14.6%
I 124379
12.3%
N 119295
11.8%
T 119295
11.8%
S 92193
9.1%
Z 74537
7.4%
M 73623
7.3%
H 69987
6.9%
U 42351
 
4.2%
F 41666
 
4.1%
Other values (5) 105711
10.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1010653
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 147616
14.6%
I 124379
12.3%
N 119295
11.8%
T 119295
11.8%
S 92193
9.1%
Z 74537
7.4%
M 73623
7.3%
H 69987
6.9%
U 42351
 
4.2%
F 41666
 
4.1%
Other values (5) 105711
10.5%

datasetName
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-03-26T16:19:37.046348image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length28
Median length28
Mean length28
Min length28

Characters and Unicode

Total characters9488836
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNMNH Material Samples (USNM)
2nd rowNMNH Material Samples (USNM)
3rd rowNMNH Material Samples (USNM)
4th rowNMNH Material Samples (USNM)
5th rowNMNH Material Samples (USNM)
ValueCountFrequency (%)
nmnh 338887
25.0%
material 338887
25.0%
samples 338887
25.0%
usnm 338887
25.0%
2025-03-26T16:19:37.133261image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 1016661
10.7%
1016661
10.7%
a 1016661
10.7%
M 1016661
10.7%
e 677774
 
7.1%
l 677774
 
7.1%
S 677774
 
7.1%
p 338887
 
3.6%
U 338887
 
3.6%
( 338887
 
3.6%
Other values (7) 2372209
25.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 9488836
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 1016661
10.7%
1016661
10.7%
a 1016661
10.7%
M 1016661
10.7%
e 677774
 
7.1%
l 677774
 
7.1%
S 677774
 
7.1%
p 338887
 
3.6%
U 338887
 
3.6%
( 338887
 
3.6%
Other values (7) 2372209
25.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 9488836
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 1016661
10.7%
1016661
10.7%
a 1016661
10.7%
M 1016661
10.7%
e 677774
 
7.1%
l 677774
 
7.1%
S 677774
 
7.1%
p 338887
 
3.6%
U 338887
 
3.6%
( 338887
 
3.6%
Other values (7) 2372209
25.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 9488836
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 1016661
10.7%
1016661
10.7%
a 1016661
10.7%
M 1016661
10.7%
e 677774
 
7.1%
l 677774
 
7.1%
S 677774
 
7.1%
p 338887
 
3.6%
U 338887
 
3.6%
( 338887
 
3.6%
Other values (7) 2372209
25.0%

basisOfRecord
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-03-26T16:19:37.167316image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters4744418
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMaterialSample
2nd rowMaterialSample
3rd rowMaterialSample
4th rowMaterialSample
5th rowMaterialSample
ValueCountFrequency (%)
materialsample 338887
100.0%
2025-03-26T16:19:37.252848image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1016661
21.4%
e 677774
14.3%
l 677774
14.3%
M 338887
 
7.1%
t 338887
 
7.1%
r 338887
 
7.1%
i 338887
 
7.1%
S 338887
 
7.1%
m 338887
 
7.1%
p 338887
 
7.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4744418
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 1016661
21.4%
e 677774
14.3%
l 677774
14.3%
M 338887
 
7.1%
t 338887
 
7.1%
r 338887
 
7.1%
i 338887
 
7.1%
S 338887
 
7.1%
m 338887
 
7.1%
p 338887
 
7.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4744418
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 1016661
21.4%
e 677774
14.3%
l 677774
14.3%
M 338887
 
7.1%
t 338887
 
7.1%
r 338887
 
7.1%
i 338887
 
7.1%
S 338887
 
7.1%
m 338887
 
7.1%
p 338887
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4744418
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 1016661
21.4%
e 677774
14.3%
l 677774
14.3%
M 338887
 
7.1%
t 338887
 
7.1%
r 338887
 
7.1%
i 338887
 
7.1%
S 338887
 
7.1%
m 338887
 
7.1%
p 338887
 
7.1%

occurrenceID
Text

Unique 

Distinct338887
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-03-26T16:19:37.433117image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length63
Median length63
Mean length63
Min length63

Characters and Unicode

Total characters21349881
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique338887 ?
Unique (%)100.0%

Sample

1st rowhttp://n2t.net/ark:/65665/300028c5f-ea1d-4c01-9253-09524fc57db6
2nd rowhttp://n2t.net/ark:/65665/30006cd83-36b3-4629-86db-f5a28307189f
3rd rowhttp://n2t.net/ark:/65665/30007a443-7a0a-49a9-9c54-cae1342160a6
4th rowhttp://n2t.net/ark:/65665/300098b69-426b-451c-a675-27a1b7bb5b60
5th rowhttp://n2t.net/ark:/65665/3000a9424-501b-43e7-a337-ee632a8fa9d0
ValueCountFrequency (%)
http://n2t.net/ark:/65665/300028c5f-ea1d-4c01-9253-09524fc57db6 1
 
< 0.1%
http://n2t.net/ark:/65665/300098b69-426b-451c-a675-27a1b7bb5b60 1
 
< 0.1%
http://n2t.net/ark:/65665/3000ef5c5-8164-4ad4-b093-79821f58ace8 1
 
< 0.1%
http://n2t.net/ark:/65665/3000ff086-55d6-4f50-81a9-fc07e565e180 1
 
< 0.1%
http://n2t.net/ark:/65665/300114e18-4d31-4558-acc1-47ce8dd8940c 1
 
< 0.1%
http://n2t.net/ark:/65665/300119514-9afd-4342-83ae-3526ac40f20f 1
 
< 0.1%
http://n2t.net/ark:/65665/300154f73-1f7a-4d73-8c43-7c6d66c03b0f 1
 
< 0.1%
http://n2t.net/ark:/65665/30015c5b5-263e-4d28-916f-89728207dfda 1
 
< 0.1%
http://n2t.net/ark:/65665/3001878d3-3d26-4b66-9ad5-77d6938de137 1
 
< 0.1%
http://n2t.net/ark:/65665/300187c30-1f5e-4401-a208-4e42206dc341 1
 
< 0.1%
Other values (338877) 338877
> 99.9%
2025-03-26T16:19:37.715967image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 1694435
 
7.9%
6 1651740
 
7.7%
- 1355548
 
6.3%
t 1355548
 
6.3%
5 1312781
 
6.1%
a 1058704
 
5.0%
4 974997
 
4.6%
3 974671
 
4.6%
2 974182
 
4.6%
e 972849
 
4.6%
Other values (16) 9024426
42.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 21349881
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
/ 1694435
 
7.9%
6 1651740
 
7.7%
- 1355548
 
6.3%
t 1355548
 
6.3%
5 1312781
 
6.1%
a 1058704
 
5.0%
4 974997
 
4.6%
3 974671
 
4.6%
2 974182
 
4.6%
e 972849
 
4.6%
Other values (16) 9024426
42.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 21349881
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
/ 1694435
 
7.9%
6 1651740
 
7.7%
- 1355548
 
6.3%
t 1355548
 
6.3%
5 1312781
 
6.1%
a 1058704
 
5.0%
4 974997
 
4.6%
3 974671
 
4.6%
2 974182
 
4.6%
e 972849
 
4.6%
Other values (16) 9024426
42.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 21349881
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
/ 1694435
 
7.9%
6 1651740
 
7.7%
- 1355548
 
6.3%
t 1355548
 
6.3%
5 1312781
 
6.1%
a 1058704
 
5.0%
4 974997
 
4.6%
3 974671
 
4.6%
2 974182
 
4.6%
e 972849
 
4.6%
Other values (16) 9024426
42.3%

catalogNumber
Text

Missing 

Distinct226280
Distinct (%)84.4%
Missing70849
Missing (%)20.9%
Memory size2.6 MiB
2025-03-26T16:19:37.861426image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length20
Mean length14.08555876
Min length9

Characters and Unicode

Total characters3775465
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique193100 ?
Unique (%)72.0%

Sample

1st rowUSNMENT00976719.2
2nd rowUSNM 1566725
3rd rowUSNM 1430312
4th rowUSNM 1477111
5th rowUSNMENT01646520
ValueCountFrequency (%)
usnm 146549
33.4%
herp 7494
 
1.7%
tissue 7202
 
1.6%
us 2196
 
0.5%
lot 2192
 
0.5%
wet 2192
 
0.5%
2192
 
0.5%
image 292
 
0.1%
594492 64
 
< 0.1%
1487948 58
 
< 0.1%
Other values (223871) 267916
61.1%
2025-03-26T16:19:38.035592image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 385135
 
10.2%
1 339458
 
9.0%
0 282740
 
7.5%
S 268039
 
7.1%
U 268038
 
7.1%
M 265842
 
7.0%
4 251273
 
6.7%
6 201786
 
5.3%
3 187823
 
5.0%
2 175282
 
4.6%
Other values (26) 1150049
30.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3775465
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 385135
 
10.2%
1 339458
 
9.0%
0 282740
 
7.5%
S 268039
 
7.1%
U 268038
 
7.1%
M 265842
 
7.0%
4 251273
 
6.7%
6 201786
 
5.3%
3 187823
 
5.0%
2 175282
 
4.6%
Other values (26) 1150049
30.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3775465
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 385135
 
10.2%
1 339458
 
9.0%
0 282740
 
7.5%
S 268039
 
7.1%
U 268038
 
7.1%
M 265842
 
7.0%
4 251273
 
6.7%
6 201786
 
5.3%
3 187823
 
5.0%
2 175282
 
4.6%
Other values (26) 1150049
30.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3775465
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 385135
 
10.2%
1 339458
 
9.0%
0 282740
 
7.5%
S 268039
 
7.1%
U 268038
 
7.1%
M 265842
 
7.0%
4 251273
 
6.7%
6 201786
 
5.3%
3 187823
 
5.0%
2 175282
 
4.6%
Other values (26) 1150049
30.5%

recordNumber
Text

Missing 

Distinct103120
Distinct (%)65.7%
Missing182004
Missing (%)53.7%
Memory size2.6 MiB
2025-03-26T16:19:38.195417image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length87
Median length53
Mean length8.258217908
Min length1

Characters and Unicode

Total characters1295574
Distinct characters76
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67384 ?
Unique (%)43.0%

Sample

1st rowT548-A9-TW19
2nd rowBMOO-09792
3rd rowJC3629
4th row707
5th rowmbio988
ValueCountFrequency (%)
blz 5373
 
2.8%
d&ml 4447
 
2.4%
1574
 
0.8%
tag 1344
 
0.7%
tree 1344
 
0.7%
flmoo 1325
 
0.7%
blb 1222
 
0.6%
sms 1218
 
0.6%
bah 992
 
0.5%
tob 838
 
0.4%
Other values (93652) 168992
89.6%
2025-03-26T16:19:38.434224image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 122994
 
9.5%
2 92881
 
7.2%
0 89424
 
6.9%
3 72505
 
5.6%
- 60980
 
4.7%
5 58053
 
4.5%
4 57710
 
4.5%
6 53844
 
4.2%
8 52886
 
4.1%
7 52361
 
4.0%
Other values (66) 581936
44.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1295574
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 122994
 
9.5%
2 92881
 
7.2%
0 89424
 
6.9%
3 72505
 
5.6%
- 60980
 
4.7%
5 58053
 
4.5%
4 57710
 
4.5%
6 53844
 
4.2%
8 52886
 
4.1%
7 52361
 
4.0%
Other values (66) 581936
44.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1295574
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 122994
 
9.5%
2 92881
 
7.2%
0 89424
 
6.9%
3 72505
 
5.6%
- 60980
 
4.7%
5 58053
 
4.5%
4 57710
 
4.5%
6 53844
 
4.2%
8 52886
 
4.1%
7 52361
 
4.0%
Other values (66) 581936
44.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1295574
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 122994
 
9.5%
2 92881
 
7.2%
0 89424
 
6.9%
3 72505
 
5.6%
- 60980
 
4.7%
5 58053
 
4.5%
4 57710
 
4.5%
6 53844
 
4.2%
8 52886
 
4.1%
7 52361
 
4.0%
Other values (66) 581936
44.9%

recordedBy
Text

Missing 

Distinct8091
Distinct (%)3.0%
Missing70286
Missing (%)20.7%
Memory size2.6 MiB
2025-03-26T16:19:38.577256image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length161
Median length107
Mean length24.15568445
Min length1

Characters and Unicode

Total characters6488241
Distinct characters83
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique911 ?
Unique (%)0.3%

Sample

1st rowR. Wielgus
2nd rowR. Vrijenhoek
3rd rowS. McPherson
4th rowK. Crandall, H. Robinson, J. Buhay & A. Toon
5th rowTibet-MacArthur, D. A. Bell, V. A. Funk, S. Ge, Y. Meng, Z. Nie, R. Ree, J. Wen, J. Yue & W. Zuo
ValueCountFrequency (%)
115745
 
8.9%
m 71131
 
5.5%
j 69105
 
5.3%
r 47308
 
3.6%
d 44114
 
3.4%
c 43688
 
3.4%
s 40895
 
3.1%
k 35511
 
2.7%
l 29182
 
2.2%
a 28449
 
2.2%
Other values (5514) 777860
59.7%
2025-03-26T16:19:38.796039image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1034387
15.9%
. 566248
 
8.7%
e 433141
 
6.7%
a 360702
 
5.6%
n 296216
 
4.6%
r 286267
 
4.4%
i 279276
 
4.3%
l 261741
 
4.0%
o 259563
 
4.0%
t 196274
 
3.0%
Other values (73) 2514426
38.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 6488241
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1034387
15.9%
. 566248
 
8.7%
e 433141
 
6.7%
a 360702
 
5.6%
n 296216
 
4.6%
r 286267
 
4.4%
i 279276
 
4.3%
l 261741
 
4.0%
o 259563
 
4.0%
t 196274
 
3.0%
Other values (73) 2514426
38.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 6488241
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1034387
15.9%
. 566248
 
8.7%
e 433141
 
6.7%
a 360702
 
5.6%
n 296216
 
4.6%
r 286267
 
4.4%
i 279276
 
4.3%
l 261741
 
4.0%
o 259563
 
4.0%
t 196274
 
3.0%
Other values (73) 2514426
38.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 6488241
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1034387
15.9%
. 566248
 
8.7%
e 433141
 
6.7%
a 360702
 
5.6%
n 296216
 
4.6%
r 286267
 
4.4%
i 279276
 
4.3%
l 261741
 
4.0%
o 259563
 
4.0%
t 196274
 
3.0%
Other values (73) 2514426
38.8%

individualCount
Text

Missing 

Distinct19
Distinct (%)< 0.1%
Missing39455
Missing (%)11.6%
Memory size2.6 MiB
2025-03-26T16:19:38.834508image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.000126907
Min length1

Characters and Unicode

Total characters299470
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)< 0.1%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1
ValueCountFrequency (%)
1 295381
98.6%
0 2669
 
0.9%
4 442
 
0.1%
2 365
 
0.1%
5 280
 
0.1%
3 226
 
0.1%
10 26
 
< 0.1%
6 20
 
< 0.1%
8 5
 
< 0.1%
7 4
 
< 0.1%
Other values (9) 14
 
< 0.1%
2025-03-26T16:19:38.924291image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 295415
98.6%
0 2699
 
0.9%
4 444
 
0.1%
2 370
 
0.1%
5 280
 
0.1%
3 229
 
0.1%
6 21
 
< 0.1%
8 5
 
< 0.1%
7 4
 
< 0.1%
9 3
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 299470
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 295415
98.6%
0 2699
 
0.9%
4 444
 
0.1%
2 370
 
0.1%
5 280
 
0.1%
3 229
 
0.1%
6 21
 
< 0.1%
8 5
 
< 0.1%
7 4
 
< 0.1%
9 3
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 299470
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 295415
98.6%
0 2699
 
0.9%
4 444
 
0.1%
2 370
 
0.1%
5 280
 
0.1%
3 229
 
0.1%
6 21
 
< 0.1%
8 5
 
< 0.1%
7 4
 
< 0.1%
9 3
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 299470
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 295415
98.6%
0 2699
 
0.9%
4 444
 
0.1%
2 370
 
0.1%
5 280
 
0.1%
3 229
 
0.1%
6 21
 
< 0.1%
8 5
 
< 0.1%
7 4
 
< 0.1%
9 3
 
< 0.1%

sex
Text

Missing 

Distinct58
Distinct (%)< 0.1%
Missing176768
Missing (%)52.2%
Memory size2.6 MiB
2025-03-26T16:19:38.955310image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length40
Median length7
Mean length6.10553359
Min length4

Characters and Unicode

Total characters989823
Distinct characters28
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)< 0.1%

Sample

1st rowUnknown
2nd rowUnknown
3rd rowUnknown
4th rowMale
5th rowUnknown
ValueCountFrequency (%)
unknown 88256
53.9%
male 41678
25.5%
female 32856
 
20.1%
worker 490
 
0.3%
sex 178
 
0.1%
hermaphrodite 73
 
< 0.1%
62
 
< 0.1%
unable 24
 
< 0.1%
to 24
 
< 0.1%
determine 24
 
< 0.1%
Other values (6) 57
 
< 0.1%
2025-03-26T16:19:39.056155image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 264838
26.8%
e 108339
10.9%
o 88854
 
9.0%
k 88746
 
9.0%
w 88746
 
9.0%
U 87804
 
8.9%
a 74679
 
7.5%
l 74606
 
7.5%
m 37388
 
3.8%
M 37280
 
3.8%
Other values (18) 38543
 
3.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 989823
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 264838
26.8%
e 108339
10.9%
o 88854
 
9.0%
k 88746
 
9.0%
w 88746
 
9.0%
U 87804
 
8.9%
a 74679
 
7.5%
l 74606
 
7.5%
m 37388
 
3.8%
M 37280
 
3.8%
Other values (18) 38543
 
3.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 989823
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 264838
26.8%
e 108339
10.9%
o 88854
 
9.0%
k 88746
 
9.0%
w 88746
 
9.0%
U 87804
 
8.9%
a 74679
 
7.5%
l 74606
 
7.5%
m 37388
 
3.8%
M 37280
 
3.8%
Other values (18) 38543
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 989823
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 264838
26.8%
e 108339
10.9%
o 88854
 
9.0%
k 88746
 
9.0%
w 88746
 
9.0%
U 87804
 
8.9%
a 74679
 
7.5%
l 74606
 
7.5%
m 37388
 
3.8%
M 37280
 
3.8%
Other values (18) 38543
 
3.9%

lifeStage
Text

Missing 

Distinct170
Distinct (%)0.1%
Missing205348
Missing (%)60.6%
Memory size2.6 MiB
2025-03-26T16:19:39.088434image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length37
Median length5
Mean length5.180591438
Min length1

Characters and Unicode

Total characters691811
Distinct characters52
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)< 0.1%

Sample

1st rowAdult
2nd rowAdult
3rd rowAdult
4th rowAdult
5th rowAdult
ValueCountFrequency (%)
adult 122138
90.4%
juvenile 3367
 
2.5%
larva 1575
 
1.2%
ii 1502
 
1.1%
flowering 1067
 
0.8%
i 884
 
0.7%
unknown 549
 
0.4%
subadult 539
 
0.4%
sterile 365
 
0.3%
eft 309
 
0.2%
Other values (90) 2768
 
2.0%
2025-03-26T16:19:39.188365image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
l 129408
18.7%
u 127910
18.5%
t 124510
18.0%
d 123037
17.8%
A 121420
17.6%
e 10365
 
1.5%
n 6947
 
1.0%
a 6313
 
0.9%
i 5976
 
0.9%
v 5446
 
0.8%
Other values (42) 30479
 
4.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 691811
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
l 129408
18.7%
u 127910
18.5%
t 124510
18.0%
d 123037
17.8%
A 121420
17.6%
e 10365
 
1.5%
n 6947
 
1.0%
a 6313
 
0.9%
i 5976
 
0.9%
v 5446
 
0.8%
Other values (42) 30479
 
4.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 691811
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
l 129408
18.7%
u 127910
18.5%
t 124510
18.0%
d 123037
17.8%
A 121420
17.6%
e 10365
 
1.5%
n 6947
 
1.0%
a 6313
 
0.9%
i 5976
 
0.9%
v 5446
 
0.8%
Other values (42) 30479
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 691811
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
l 129408
18.7%
u 127910
18.5%
t 124510
18.0%
d 123037
17.8%
A 121420
17.6%
e 10365
 
1.5%
n 6947
 
1.0%
a 6313
 
0.9%
i 5976
 
0.9%
v 5446
 
0.8%
Other values (42) 30479
 
4.4%

occurrenceStatus
Text

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-03-26T16:19:39.217023image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters2372209
Distinct characters6
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowpresent
2nd rowpresent
3rd rowpresent
4th rowpresent
5th rowpresent
ValueCountFrequency (%)
present 338887
100.0%
2025-03-26T16:19:39.299325image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 677774
28.6%
p 338887
14.3%
r 338887
14.3%
s 338887
14.3%
n 338887
14.3%
t 338887
14.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2372209
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 677774
28.6%
p 338887
14.3%
r 338887
14.3%
s 338887
14.3%
n 338887
14.3%
t 338887
14.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2372209
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 677774
28.6%
p 338887
14.3%
r 338887
14.3%
s 338887
14.3%
n 338887
14.3%
t 338887
14.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2372209
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 677774
28.6%
p 338887
14.3%
r 338887
14.3%
s 338887
14.3%
n 338887
14.3%
t 338887
14.3%

preparations
Text

Missing 

Distinct34
Distinct (%)< 0.1%
Missing251707
Missing (%)74.3%
Memory size2.6 MiB
2025-03-26T16:19:39.331788image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length142
Median length6
Mean length6.192245928
Min length4

Characters and Unicode

Total characters539840
Distinct characters47
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowFrozen
2nd rowFrozen
3rd rowFrozen
4th rowFrozen
5th rowFrozen
ValueCountFrequency (%)
frozen 72728
79.3%
vial 6709
 
7.3%
ethanol 4931
 
5.4%
wet 2273
 
2.5%
lot 2273
 
2.5%
drained 1067
 
1.2%
photograph 626
 
0.7%
biorepository 456
 
0.5%
alcohol 198
 
0.2%
148
 
0.2%
Other values (11) 295
 
0.3%
2025-03-26T16:19:39.427474image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 83093
15.4%
n 78823
14.6%
e 76580
14.2%
r 75391
14.0%
z 72728
13.5%
F 72377
13.4%
l 14364
 
2.7%
a 13345
 
2.5%
t 10614
 
2.0%
i 8788
 
1.6%
Other values (37) 33737
6.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 539840
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 83093
15.4%
n 78823
14.6%
e 76580
14.2%
r 75391
14.0%
z 72728
13.5%
F 72377
13.4%
l 14364
 
2.7%
a 13345
 
2.5%
t 10614
 
2.0%
i 8788
 
1.6%
Other values (37) 33737
6.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 539840
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 83093
15.4%
n 78823
14.6%
e 76580
14.2%
r 75391
14.0%
z 72728
13.5%
F 72377
13.4%
l 14364
 
2.7%
a 13345
 
2.5%
t 10614
 
2.0%
i 8788
 
1.6%
Other values (37) 33737
6.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 539840
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 83093
15.4%
n 78823
14.6%
e 76580
14.2%
r 75391
14.0%
z 72728
13.5%
F 72377
13.4%
l 14364
 
2.7%
a 13345
 
2.5%
t 10614
 
2.0%
i 8788
 
1.6%
Other values (37) 33737
6.2%
Distinct4
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size2.6 MiB
2025-03-26T16:19:39.457511image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length13
Median length13
Mean length12.38343165
Min length2

Characters and Unicode

Total characters4196584
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowin collection
2nd rowin collection
3rd rowin collection
4th rowin collection
5th rowin collection
ValueCountFrequency (%)
in 299029
46.9%
collection 299029
46.9%
consumed 38091
 
6.0%
yes 945
 
0.1%
no 822
 
0.1%
2025-03-26T16:19:39.635174image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 636971
15.2%
o 636971
15.2%
c 636149
15.2%
i 598058
14.3%
l 598058
14.3%
e 338065
8.1%
299029
7.1%
t 299029
7.1%
s 39036
 
0.9%
u 38091
 
0.9%
Other values (3) 77127
 
1.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4196584
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
n 636971
15.2%
o 636971
15.2%
c 636149
15.2%
i 598058
14.3%
l 598058
14.3%
e 338065
8.1%
299029
7.1%
t 299029
7.1%
s 39036
 
0.9%
u 38091
 
0.9%
Other values (3) 77127
 
1.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4196584
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
n 636971
15.2%
o 636971
15.2%
c 636149
15.2%
i 598058
14.3%
l 598058
14.3%
e 338065
8.1%
299029
7.1%
t 299029
7.1%
s 39036
 
0.9%
u 38091
 
0.9%
Other values (3) 77127
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4196584
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
n 636971
15.2%
o 636971
15.2%
c 636149
15.2%
i 598058
14.3%
l 598058
14.3%
e 338065
8.1%
299029
7.1%
t 299029
7.1%
s 39036
 
0.9%
u 38091
 
0.9%
Other values (3) 77127
 
1.8%

associatedMedia
Text

Missing 

Distinct11578
Distinct (%)79.4%
Missing324297
Missing (%)95.7%
Memory size2.6 MiB
2025-03-26T16:19:39.711336image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length369
Median length49
Mean length52.44962303
Min length49

Characters and Unicode

Total characters765240
Distinct characters31
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9293 ?
Unique (%)63.7%

Sample

1st rowhttps://collections.nmnh.si.edu/media/?i=15102863
2nd rowhttps://collections.nmnh.si.edu/media/?i=15392053
3rd rowhttps://collections.nmnh.si.edu/media/?i=15102609
4th rowhttps://collections.nmnh.si.edu/media/?i=15102164
5th rowhttps://collections.nmnh.si.edu/media/?i=15100806
ValueCountFrequency (%)
https://collections.nmnh.si.edu/media/?i=16192884 83
 
0.4%
https://collections.nmnh.si.edu/media/?i=14723169 38
 
0.2%
14723158 38
 
0.2%
https://collections.nmnh.si.edu/media/?i=13853473 34
 
0.2%
https://collections.nmnh.si.edu/media/?i=14322468 30
 
0.2%
https://collections.nmnh.si.edu/media/?i=13822124 28
 
0.1%
https://collections.nmnh.si.edu/media/?i=13812175 28
 
0.1%
https://collections.nmnh.si.edu/media/?i=13812183 28
 
0.1%
https://collections.nmnh.si.edu/media/?i=13812196 24
 
0.1%
https://collections.nmnh.si.edu/media/?i=13858205 22
 
0.1%
Other values (14633) 19270
98.2%
2025-03-26T16:19:39.864443image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 58360
 
7.6%
/ 58360
 
7.6%
t 43770
 
5.7%
s 43770
 
5.7%
. 43770
 
5.7%
n 43770
 
5.7%
e 43770
 
5.7%
1 38976
 
5.1%
d 29180
 
3.8%
m 29180
 
3.8%
Other values (21) 332334
43.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 765240
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 58360
 
7.6%
/ 58360
 
7.6%
t 43770
 
5.7%
s 43770
 
5.7%
. 43770
 
5.7%
n 43770
 
5.7%
e 43770
 
5.7%
1 38976
 
5.1%
d 29180
 
3.8%
m 29180
 
3.8%
Other values (21) 332334
43.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 765240
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 58360
 
7.6%
/ 58360
 
7.6%
t 43770
 
5.7%
s 43770
 
5.7%
. 43770
 
5.7%
n 43770
 
5.7%
e 43770
 
5.7%
1 38976
 
5.1%
d 29180
 
3.8%
m 29180
 
3.8%
Other values (21) 332334
43.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 765240
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 58360
 
7.6%
/ 58360
 
7.6%
t 43770
 
5.7%
s 43770
 
5.7%
. 43770
 
5.7%
n 43770
 
5.7%
e 43770
 
5.7%
1 38976
 
5.1%
d 29180
 
3.8%
m 29180
 
3.8%
Other values (21) 332334
43.4%

associatedSequences
Text

Missing 

Distinct25169
Distinct (%)76.9%
Missing306152
Missing (%)90.3%
Memory size2.6 MiB
2025-03-26T16:19:40.027293image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length228
Median length8
Mean length11.35698793
Min length8

Characters and Unicode

Total characters371771
Distinct characters35
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17603 ?
Unique (%)53.8%

Sample

1st rowMW204230; MW124559
2nd rowMW982336
3rd rowMF785606; MF785913
4th rowMN344605
5th rowJQ840329
ValueCountFrequency (%)
prjna345052 17
 
< 0.1%
prjna396973 12
 
< 0.1%
mw983652 2
 
< 0.1%
mw277951 2
 
< 0.1%
mn344859 2
 
< 0.1%
mn345804 2
 
< 0.1%
mg967767 2
 
< 0.1%
mn344210 2
 
< 0.1%
mw982140 2
 
< 0.1%
mn345457 2
 
< 0.1%
Other values (35832) 43453
99.9%
2025-03-26T16:19:40.277692image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8 34064
 
9.2%
3 32638
 
8.8%
4 30987
 
8.3%
9 27708
 
7.5%
M 27290
 
7.3%
2 27116
 
7.3%
7 23976
 
6.4%
0 23224
 
6.2%
5 21391
 
5.8%
1 21140
 
5.7%
Other values (25) 102237
27.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 371771
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
8 34064
 
9.2%
3 32638
 
8.8%
4 30987
 
8.3%
9 27708
 
7.5%
M 27290
 
7.3%
2 27116
 
7.3%
7 23976
 
6.4%
0 23224
 
6.2%
5 21391
 
5.8%
1 21140
 
5.7%
Other values (25) 102237
27.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 371771
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
8 34064
 
9.2%
3 32638
 
8.8%
4 30987
 
8.3%
9 27708
 
7.5%
M 27290
 
7.3%
2 27116
 
7.3%
7 23976
 
6.4%
0 23224
 
6.2%
5 21391
 
5.8%
1 21140
 
5.7%
Other values (25) 102237
27.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 371771
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
8 34064
 
9.2%
3 32638
 
8.8%
4 30987
 
8.3%
9 27708
 
7.5%
M 27290
 
7.3%
2 27116
 
7.3%
7 23976
 
6.4%
0 23224
 
6.2%
5 21391
 
5.8%
1 21140
 
5.7%
Other values (25) 102237
27.5%

occurrenceRemarks
Text

Missing 

Distinct28725
Distinct (%)19.8%
Missing194011
Missing (%)57.2%
Memory size2.6 MiB
2025-03-26T16:19:40.439480image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length1168
Median length61
Mean length76.53942682
Min length1

Characters and Unicode

Total characters11088726
Distinct characters101
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19983 ?
Unique (%)13.8%

Sample

1st rowOne leg removed for genetic sampling while on loan to GUELPH.
2nd rowOrder: 10948; Box Number: MBARI_0136: Box Position: B/4
3rd rowOne leg removed for genetic sampling while on loan to GUELPH.
4th rowOriginally cataloged as an image record because field notes indicated there was a photovoucher for the specimen. When the images were cataloged in early 2020, no photos were found for this specimen so the record was changed to a Genetic Sample (DNA) with no voucher.
5th rowEntire tissue sample consumed for DNA extraction. Specimen voucher located at Museum National d'Histoire Naturelle, Paris.
ValueCountFrequency (%)
for 114838
 
6.2%
on 113378
 
6.1%
to 111927
 
6.0%
genetic 110770
 
6.0%
while 109786
 
5.9%
sampling 108913
 
5.9%
loan 108870
 
5.9%
removed 108857
 
5.9%
guelph 108797
 
5.9%
one 105620
 
5.7%
Other values (33189) 753914
40.6%
2025-03-26T16:19:40.665331image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1710794
15.4%
e 1078740
 
9.7%
o 778432
 
7.0%
n 696574
 
6.3%
l 576184
 
5.2%
i 556238
 
5.0%
a 421874
 
3.8%
r 400699
 
3.6%
t 398843
 
3.6%
g 356623
 
3.2%
Other values (91) 4113725
37.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 11088726
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1710794
15.4%
e 1078740
 
9.7%
o 778432
 
7.0%
n 696574
 
6.3%
l 576184
 
5.2%
i 556238
 
5.0%
a 421874
 
3.8%
r 400699
 
3.6%
t 398843
 
3.6%
g 356623
 
3.2%
Other values (91) 4113725
37.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 11088726
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1710794
15.4%
e 1078740
 
9.7%
o 778432
 
7.0%
n 696574
 
6.3%
l 576184
 
5.2%
i 556238
 
5.0%
a 421874
 
3.8%
r 400699
 
3.6%
t 398843
 
3.6%
g 356623
 
3.2%
Other values (91) 4113725
37.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 11088726
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1710794
15.4%
e 1078740
 
9.7%
o 778432
 
7.0%
n 696574
 
6.3%
l 576184
 
5.2%
i 556238
 
5.0%
a 421874
 
3.8%
r 400699
 
3.6%
t 398843
 
3.6%
g 356623
 
3.2%
Other values (91) 4113725
37.1%

materialSampleID
Text

Missing 

Distinct253713
Distinct (%)100.0%
Missing85174
Missing (%)25.1%
Memory size2.6 MiB
2025-03-26T16:19:40.903994image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters1775991
Distinct characters36
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique253713 ?
Unique (%)100.0%

Sample

1st rowAR5TC43
2nd rowAL2IC84
3rd rowAF9HI08
4th rowAD5JZ99
5th rowAE0OQ35
ValueCountFrequency (%)
ar5tc43 1
 
< 0.1%
am1rc30 1
 
< 0.1%
an9jb30 1
 
< 0.1%
af9hi08 1
 
< 0.1%
ad5jz99 1
 
< 0.1%
ae0oq35 1
 
< 0.1%
an7hd65 1
 
< 0.1%
ak3zy87 1
 
< 0.1%
ap6aq38 1
 
< 0.1%
am4uq13 1
 
< 0.1%
Other values (253703) 253703
> 99.9%
2025-03-26T16:19:41.185494image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 288325
 
16.2%
7 79993
 
4.5%
1 78070
 
4.4%
2 77436
 
4.4%
0 77220
 
4.3%
4 76782
 
4.3%
5 76531
 
4.3%
3 76190
 
4.3%
9 75168
 
4.2%
6 73797
 
4.2%
Other values (26) 796479
44.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1775991
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
A 288325
 
16.2%
7 79993
 
4.5%
1 78070
 
4.4%
2 77436
 
4.4%
0 77220
 
4.3%
4 76782
 
4.3%
5 76531
 
4.3%
3 76190
 
4.3%
9 75168
 
4.2%
6 73797
 
4.2%
Other values (26) 796479
44.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1775991
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
A 288325
 
16.2%
7 79993
 
4.5%
1 78070
 
4.4%
2 77436
 
4.4%
0 77220
 
4.3%
4 76782
 
4.3%
5 76531
 
4.3%
3 76190
 
4.3%
9 75168
 
4.2%
6 73797
 
4.2%
Other values (26) 796479
44.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1775991
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
A 288325
 
16.2%
7 79993
 
4.5%
1 78070
 
4.4%
2 77436
 
4.4%
0 77220
 
4.3%
4 76782
 
4.3%
5 76531
 
4.3%
3 76190
 
4.3%
9 75168
 
4.2%
6 73797
 
4.2%
Other values (26) 796479
44.8%

fieldNumber
Text

Missing 

Distinct7067
Distinct (%)9.9%
Missing267780
Missing (%)79.0%
Memory size2.6 MiB
2025-03-26T16:19:41.342458image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length56
Median length43
Mean length11.55260382
Min length1

Characters and Unicode

Total characters821471
Distinct characters72
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2661 ?
Unique (%)3.7%

Sample

1st rowMBARI/T548
2nd rowMBIO/BIZ-231
3rd rowMoorea F-06-12
4th rowMBARI/T488
5th rowAL-4097
ValueCountFrequency (%)
cb 3404
 
3.7%
moorea 3162
 
3.5%
fp 1218
 
1.3%
lrp 1035
 
1.1%
bah 992
 
1.1%
tob 838
 
0.9%
cur 813
 
0.9%
mbio/080611_minv_014 627
 
0.7%
dgs 507
 
0.6%
f-06-05 504
 
0.6%
Other values (7238) 78186
85.6%
2025-03-26T16:19:41.559770image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 78794
 
9.6%
- 70278
 
8.6%
1 62426
 
7.6%
B 45995
 
5.6%
2 44088
 
5.4%
I 35515
 
4.3%
M 34466
 
4.2%
A 34211
 
4.2%
3 27109
 
3.3%
8 21704
 
2.6%
Other values (62) 366885
44.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 821471
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 78794
 
9.6%
- 70278
 
8.6%
1 62426
 
7.6%
B 45995
 
5.6%
2 44088
 
5.4%
I 35515
 
4.3%
M 34466
 
4.2%
A 34211
 
4.2%
3 27109
 
3.3%
8 21704
 
2.6%
Other values (62) 366885
44.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 821471
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 78794
 
9.6%
- 70278
 
8.6%
1 62426
 
7.6%
B 45995
 
5.6%
2 44088
 
5.4%
I 35515
 
4.3%
M 34466
 
4.2%
A 34211
 
4.2%
3 27109
 
3.3%
8 21704
 
2.6%
Other values (62) 366885
44.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 821471
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 78794
 
9.6%
- 70278
 
8.6%
1 62426
 
7.6%
B 45995
 
5.6%
2 44088
 
5.4%
I 35515
 
4.3%
M 34466
 
4.2%
A 34211
 
4.2%
3 27109
 
3.3%
8 21704
 
2.6%
Other values (62) 366885
44.7%

eventDate
Text

Missing 

Distinct23061
Distinct (%)7.2%
Missing16375
Missing (%)4.8%
Memory size2.6 MiB
2025-03-26T16:19:41.678016image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length10
Mean length11.08435345
Min length4

Characters and Unicode

Total characters3574837
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1365 ?
Unique (%)0.4%

Sample

1st row1977-05-21
2nd row2003-04-05
3rd row2009-12-05
4th row2006-09-14
5th row2003-05-01/2003-05-13
ValueCountFrequency (%)
2018-03-19/2018-03-23 1123
 
0.3%
2016-02-22/2016-03-09 844
 
0.3%
2008-06-11 650
 
0.2%
2017-05-26 624
 
0.2%
2015-05-09 524
 
0.2%
2017-05-23 520
 
0.2%
2017-05-30 515
 
0.2%
2006-03-12 514
 
0.2%
2017-08-14 508
 
0.2%
2017-05-27 505
 
0.2%
Other values (23049) 316237
98.0%
2025-03-26T16:19:41.870782image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 773996
21.7%
- 705777
19.7%
1 578475
16.2%
2 414630
11.6%
9 303213
 
8.5%
8 151888
 
4.2%
7 140605
 
3.9%
6 131577
 
3.7%
5 124129
 
3.5%
3 120397
 
3.4%
Other values (6) 130150
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3574837
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 773996
21.7%
- 705777
19.7%
1 578475
16.2%
2 414630
11.6%
9 303213
 
8.5%
8 151888
 
4.2%
7 140605
 
3.9%
6 131577
 
3.7%
5 124129
 
3.5%
3 120397
 
3.4%
Other values (6) 130150
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3574837
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 773996
21.7%
- 705777
19.7%
1 578475
16.2%
2 414630
11.6%
9 303213
 
8.5%
8 151888
 
4.2%
7 140605
 
3.9%
6 131577
 
3.7%
5 124129
 
3.5%
3 120397
 
3.4%
Other values (6) 130150
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3574837
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 773996
21.7%
- 705777
19.7%
1 578475
16.2%
2 414630
11.6%
9 303213
 
8.5%
8 151888
 
4.2%
7 140605
 
3.9%
6 131577
 
3.7%
5 124129
 
3.5%
3 120397
 
3.4%
Other values (6) 130150
 
3.6%

startDayOfYear
Text

Missing 

Distinct366
Distinct (%)0.1%
Missing18139
Missing (%)5.4%
Memory size2.6 MiB
2025-03-26T16:19:42.022195image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.771929989
Min length1

Characters and Unicode

Total characters889091
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row141
2nd row95
3rd row339
4th row257
5th row121
ValueCountFrequency (%)
142 2419
 
0.8%
78 1970
 
0.6%
140 1912
 
0.6%
201 1848
 
0.6%
147 1848
 
0.6%
152 1832
 
0.6%
197 1823
 
0.6%
182 1815
 
0.6%
150 1811
 
0.6%
146 1796
 
0.6%
Other values (356) 301674
94.1%
2025-03-26T16:19:42.231827image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 193699
21.8%
2 157935
17.8%
3 100985
11.4%
4 66431
 
7.5%
5 65555
 
7.4%
7 63729
 
7.2%
0 61202
 
6.9%
6 61155
 
6.9%
8 59991
 
6.7%
9 58409
 
6.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 889091
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 193699
21.8%
2 157935
17.8%
3 100985
11.4%
4 66431
 
7.5%
5 65555
 
7.4%
7 63729
 
7.2%
0 61202
 
6.9%
6 61155
 
6.9%
8 59991
 
6.7%
9 58409
 
6.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 889091
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 193699
21.8%
2 157935
17.8%
3 100985
11.4%
4 66431
 
7.5%
5 65555
 
7.4%
7 63729
 
7.2%
0 61202
 
6.9%
6 61155
 
6.9%
8 59991
 
6.7%
9 58409
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 889091
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 193699
21.8%
2 157935
17.8%
3 100985
11.4%
4 66431
 
7.5%
5 65555
 
7.4%
7 63729
 
7.2%
0 61202
 
6.9%
6 61155
 
6.9%
8 59991
 
6.7%
9 58409
 
6.6%

endDayOfYear
Text

Missing 

Distinct366
Distinct (%)0.1%
Missing17919
Missing (%)5.3%
Memory size2.6 MiB
2025-03-26T16:19:42.377377image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.778731836
Min length1

Characters and Unicode

Total characters891884
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row141
2nd row95
3rd row339
4th row257
5th row133
ValueCountFrequency (%)
142 2350
 
0.7%
151 2070
 
0.6%
150 2022
 
0.6%
82 1902
 
0.6%
212 1893
 
0.6%
143 1867
 
0.6%
69 1866
 
0.6%
197 1802
 
0.6%
146 1797
 
0.6%
147 1757
 
0.5%
Other values (356) 301642
94.0%
2025-03-26T16:19:42.589540image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 190183
21.3%
2 159961
17.9%
3 102008
11.4%
4 67395
 
7.6%
5 65338
 
7.3%
0 63243
 
7.1%
6 62203
 
7.0%
7 62028
 
7.0%
8 60038
 
6.7%
9 59487
 
6.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 891884
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 190183
21.3%
2 159961
17.9%
3 102008
11.4%
4 67395
 
7.6%
5 65338
 
7.3%
0 63243
 
7.1%
6 62203
 
7.0%
7 62028
 
7.0%
8 60038
 
6.7%
9 59487
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 891884
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 190183
21.3%
2 159961
17.9%
3 102008
11.4%
4 67395
 
7.6%
5 65338
 
7.3%
0 63243
 
7.1%
6 62203
 
7.0%
7 62028
 
7.0%
8 60038
 
6.7%
9 59487
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 891884
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 190183
21.3%
2 159961
17.9%
3 102008
11.4%
4 67395
 
7.6%
5 65338
 
7.3%
0 63243
 
7.1%
6 62203
 
7.0%
7 62028
 
7.0%
8 60038
 
6.7%
9 59487
 
6.7%

year
Text

Missing 

Distinct158
Distinct (%)< 0.1%
Missing16375
Missing (%)4.8%
Memory size2.6 MiB
2025-03-26T16:19:42.695397image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters1290048
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st row1977
2nd row2003
3rd row2009
4th row2006
5th row2003
ValueCountFrequency (%)
2009 14284
 
4.4%
2017 14084
 
4.4%
2015 13837
 
4.3%
2010 13766
 
4.3%
2012 12241
 
3.8%
2008 12004
 
3.7%
2016 11475
 
3.6%
2018 11100
 
3.4%
2019 9921
 
3.1%
2006 9474
 
2.9%
Other values (148) 200326
62.1%
2025-03-26T16:19:42.846921image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 296680
23.0%
1 275318
21.3%
2 223388
17.3%
9 214855
16.7%
8 70682
 
5.5%
7 60311
 
4.7%
6 50436
 
3.9%
5 38217
 
3.0%
3 30616
 
2.4%
4 29545
 
2.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1290048
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 296680
23.0%
1 275318
21.3%
2 223388
17.3%
9 214855
16.7%
8 70682
 
5.5%
7 60311
 
4.7%
6 50436
 
3.9%
5 38217
 
3.0%
3 30616
 
2.4%
4 29545
 
2.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1290048
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 296680
23.0%
1 275318
21.3%
2 223388
17.3%
9 214855
16.7%
8 70682
 
5.5%
7 60311
 
4.7%
6 50436
 
3.9%
5 38217
 
3.0%
3 30616
 
2.4%
4 29545
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1290048
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 296680
23.0%
1 275318
21.3%
2 223388
17.3%
9 214855
16.7%
8 70682
 
5.5%
7 60311
 
4.7%
6 50436
 
3.9%
5 38217
 
3.0%
3 30616
 
2.4%
4 29545
 
2.3%

month
Text

Missing 

Distinct12
Distinct (%)< 0.1%
Missing17976
Missing (%)5.3%
Memory size2.6 MiB
2025-03-26T16:19:42.890459image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length1
Mean length1.178217637
Min length1

Characters and Unicode

Total characters378103
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row4
3rd row12
4th row9
5th row5
ValueCountFrequency (%)
5 42874
13.4%
6 37449
11.7%
7 37048
11.5%
8 30912
9.6%
4 28946
9.0%
3 27581
8.6%
9 25650
8.0%
10 23464
7.3%
11 20405
6.4%
2 16901
 
5.3%
Other values (2) 29681
9.2%
2025-03-26T16:19:42.977732image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 93955
24.8%
5 42874
11.3%
6 37449
 
9.9%
7 37048
 
9.8%
8 30912
 
8.2%
2 30224
 
8.0%
4 28946
 
7.7%
3 27581
 
7.3%
9 25650
 
6.8%
0 23464
 
6.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 378103
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 93955
24.8%
5 42874
11.3%
6 37449
 
9.9%
7 37048
 
9.8%
8 30912
 
8.2%
2 30224
 
8.0%
4 28946
 
7.7%
3 27581
 
7.3%
9 25650
 
6.8%
0 23464
 
6.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 378103
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 93955
24.8%
5 42874
11.3%
6 37449
 
9.9%
7 37048
 
9.8%
8 30912
 
8.2%
2 30224
 
8.0%
4 28946
 
7.7%
3 27581
 
7.3%
9 25650
 
6.8%
0 23464
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 378103
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 93955
24.8%
5 42874
11.3%
6 37449
 
9.9%
7 37048
 
9.8%
8 30912
 
8.2%
2 30224
 
8.0%
4 28946
 
7.7%
3 27581
 
7.3%
9 25650
 
6.8%
0 23464
 
6.2%

day
Text

Missing 

Distinct31
Distinct (%)< 0.1%
Missing19395
Missing (%)5.7%
Memory size2.6 MiB
2025-03-26T16:19:43.021360image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length2
Median length2
Mean length1.689813829
Min length1

Characters and Unicode

Total characters539882
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row21
2nd row5
3rd row5
4th row14
5th row1
ValueCountFrequency (%)
1 18070
 
5.7%
15 11517
 
3.6%
11 11325
 
3.5%
12 11315
 
3.5%
5 11224
 
3.5%
22 11204
 
3.5%
16 11196
 
3.5%
10 11192
 
3.5%
8 10979
 
3.4%
19 10637
 
3.3%
Other values (21) 200833
62.9%
2025-03-26T16:19:43.117564image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 151152
28.0%
2 130563
24.2%
3 43066
 
8.0%
8 32101
 
5.9%
5 31777
 
5.9%
6 30939
 
5.7%
9 30466
 
5.6%
0 30325
 
5.6%
7 30112
 
5.6%
4 29381
 
5.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 539882
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1 151152
28.0%
2 130563
24.2%
3 43066
 
8.0%
8 32101
 
5.9%
5 31777
 
5.9%
6 30939
 
5.7%
9 30466
 
5.6%
0 30325
 
5.6%
7 30112
 
5.6%
4 29381
 
5.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 539882
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1 151152
28.0%
2 130563
24.2%
3 43066
 
8.0%
8 32101
 
5.9%
5 31777
 
5.9%
6 30939
 
5.7%
9 30466
 
5.6%
0 30325
 
5.6%
7 30112
 
5.6%
4 29381
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 539882
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1 151152
28.0%
2 130563
24.2%
3 43066
 
8.0%
8 32101
 
5.9%
5 31777
 
5.9%
6 30939
 
5.7%
9 30466
 
5.6%
0 30325
 
5.6%
7 30112
 
5.6%
4 29381
 
5.4%

verbatimEventDate
Text

Missing 

Distinct10235
Distinct (%)10.0%
Missing236393
Missing (%)69.8%
Memory size2.6 MiB
2025-03-26T16:19:43.246891image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length72
Median length71
Mean length13.69916288
Min length1

Characters and Unicode

Total characters1404082
Distinct characters76
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2666 ?
Unique (%)2.6%

Sample

1st row4/5/2003 3:59:00 PM
2nd row2007 or prior, based on filename of source data sheet
3rd row14 Sep 2006
4th row10/11/2002 1:30:00 PM
5th row11 May 2014
ValueCountFrequency (%)
may 10980
 
3.6%
apr 6730
 
2.2%
pm 6659
 
2.2%
aug 5896
 
1.9%
5385
 
1.8%
2007 5238
 
1.7%
sep 5193
 
1.7%
mar 4916
 
1.6%
2008 4667
 
1.5%
june 4035
 
1.3%
Other values (3777) 243455
80.3%
2025-03-26T16:19:43.470950image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
200660
 
14.3%
0 159336
 
11.3%
1 143671
 
10.2%
2 117979
 
8.4%
9 73354
 
5.2%
e 41039
 
2.9%
8 37376
 
2.7%
a 35891
 
2.6%
3 32923
 
2.3%
r 32356
 
2.3%
Other values (66) 529497
37.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1404082
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
200660
 
14.3%
0 159336
 
11.3%
1 143671
 
10.2%
2 117979
 
8.4%
9 73354
 
5.2%
e 41039
 
2.9%
8 37376
 
2.7%
a 35891
 
2.6%
3 32923
 
2.3%
r 32356
 
2.3%
Other values (66) 529497
37.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1404082
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
200660
 
14.3%
0 159336
 
11.3%
1 143671
 
10.2%
2 117979
 
8.4%
9 73354
 
5.2%
e 41039
 
2.9%
8 37376
 
2.7%
a 35891
 
2.6%
3 32923
 
2.3%
r 32356
 
2.3%
Other values (66) 529497
37.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1404082
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
200660
 
14.3%
0 159336
 
11.3%
1 143671
 
10.2%
2 117979
 
8.4%
9 73354
 
5.2%
e 41039
 
2.9%
8 37376
 
2.7%
a 35891
 
2.6%
3 32923
 
2.3%
r 32356
 
2.3%
Other values (66) 529497
37.7%

habitat
Text

Missing 

Distinct5078
Distinct (%)14.0%
Missing302736
Missing (%)89.3%
Memory size2.6 MiB
2025-03-26T16:19:43.614577image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length382
Median length180
Mean length39.97828552
Min length1

Characters and Unicode

Total characters1445255
Distinct characters87
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1916 ?
Unique (%)5.3%

Sample

1st rowRocky slope with scattered shrubs. Moist soil on slope
2nd rowScrubland
3rd rowEcological remarks by collector(s): yes
4th rowCultivated/garden
5th rowbrushed from under rubble
ValueCountFrequency (%)
forest 9256
 
4.6%
and 8097
 
4.0%
with 6453
 
3.2%
by 4858
 
2.4%
ecological 4353
 
2.2%
remarks 4353
 
2.2%
collector(s 4348
 
2.1%
in 4307
 
2.1%
yes 3551
 
1.8%
slopes 2428
 
1.2%
Other values (4259) 150413
74.3%
2025-03-26T16:19:43.850129image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
166266
 
11.5%
e 123190
 
8.5%
a 115293
 
8.0%
r 98015
 
6.8%
o 97255
 
6.7%
s 87903
 
6.1%
i 77312
 
5.3%
n 74104
 
5.1%
t 69325
 
4.8%
l 65467
 
4.5%
Other values (77) 471125
32.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1445255
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
166266
 
11.5%
e 123190
 
8.5%
a 115293
 
8.0%
r 98015
 
6.8%
o 97255
 
6.7%
s 87903
 
6.1%
i 77312
 
5.3%
n 74104
 
5.1%
t 69325
 
4.8%
l 65467
 
4.5%
Other values (77) 471125
32.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1445255
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
166266
 
11.5%
e 123190
 
8.5%
a 115293
 
8.0%
r 98015
 
6.8%
o 97255
 
6.7%
s 87903
 
6.1%
i 77312
 
5.3%
n 74104
 
5.1%
t 69325
 
4.8%
l 65467
 
4.5%
Other values (77) 471125
32.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1445255
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
166266
 
11.5%
e 123190
 
8.5%
a 115293
 
8.0%
r 98015
 
6.8%
o 97255
 
6.7%
s 87903
 
6.1%
i 77312
 
5.3%
n 74104
 
5.1%
t 69325
 
4.8%
l 65467
 
4.5%
Other values (77) 471125
32.6%

locationID
Text

Missing 

Distinct4571
Distinct (%)8.5%
Missing285298
Missing (%)84.2%
Memory size2.6 MiB
2025-03-26T16:19:44.010456image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length32
Median length28
Mean length6.812760081
Min length1

Characters and Unicode

Total characters365089
Distinct characters83
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1195 ?
Unique (%)2.2%

Sample

1st rowT548
2nd rowBIZ-231
3rd rowT488
4th row02-10
5th rowVES117
ValueCountFrequency (%)
080611_minv_014 628
 
1.1%
site 469
 
0.8%
i 458
 
0.8%
trawl 457
 
0.8%
serc 326
 
0.6%
14 313
 
0.5%
v1951 309
 
0.5%
080608_minv_012 289
 
0.5%
10 276
 
0.5%
21 276
 
0.5%
Other values (4452) 53151
93.3%
2025-03-26T16:19:44.344582image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 37222
 
10.2%
1 34764
 
9.5%
- 19233
 
5.3%
2 18321
 
5.0%
I 15986
 
4.4%
_ 15406
 
4.2%
5 13808
 
3.8%
4 13718
 
3.8%
8 13292
 
3.6%
6 12697
 
3.5%
Other values (73) 170642
46.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 365089
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 37222
 
10.2%
1 34764
 
9.5%
- 19233
 
5.3%
2 18321
 
5.0%
I 15986
 
4.4%
_ 15406
 
4.2%
5 13808
 
3.8%
4 13718
 
3.8%
8 13292
 
3.6%
6 12697
 
3.5%
Other values (73) 170642
46.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 365089
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 37222
 
10.2%
1 34764
 
9.5%
- 19233
 
5.3%
2 18321
 
5.0%
I 15986
 
4.4%
_ 15406
 
4.2%
5 13808
 
3.8%
4 13718
 
3.8%
8 13292
 
3.6%
6 12697
 
3.5%
Other values (73) 170642
46.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 365089
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 37222
 
10.2%
1 34764
 
9.5%
- 19233
 
5.3%
2 18321
 
5.0%
I 15986
 
4.4%
_ 15406
 
4.2%
5 13808
 
3.8%
4 13718
 
3.8%
8 13292
 
3.6%
6 12697
 
3.5%
Other values (73) 170642
46.7%

higherGeography
Text

Missing 

Distinct7780
Distinct (%)2.3%
Missing4532
Missing (%)1.3%
Memory size2.6 MiB
2025-03-26T16:19:44.491581image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length128
Median length103
Mean length44.48443122
Min length4

Characters and Unicode

Total characters14873592
Distinct characters98
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique787 ?
Unique (%)0.2%

Sample

1st rowUnited States, Arizona, Cochise
2nd rowNorth Pacific Ocean, Gulf of California, Mexico
3rd rowSouth Pacific Ocean, French Polynesia, Society Islands, Moorea
4th rowUnited States, Arkansas
5th rowAsia-Temperate, China, Xizang, Nielamu (Nyalam) Xian
ValueCountFrequency (%)
states 151050
 
7.6%
united 150972
 
7.6%
north 102077
 
5.1%
ocean 69584
 
3.5%
pacific 66427
 
3.4%
america 65599
 
3.3%
not 60437
 
3.0%
stated 60437
 
3.0%
islands 44200
 
2.2%
atlantic 41486
 
2.1%
Other values (4525) 1169998
59.0%
2025-03-26T16:19:44.716251image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1647912
 
11.1%
a 1475775
 
9.9%
t 1110607
 
7.5%
e 1086910
 
7.3%
i 1043240
 
7.0%
n 863061
 
5.8%
, 827656
 
5.6%
o 732955
 
4.9%
r 621528
 
4.2%
s 543168
 
3.7%
Other values (88) 4920780
33.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 14873592
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1647912
 
11.1%
a 1475775
 
9.9%
t 1110607
 
7.5%
e 1086910
 
7.3%
i 1043240
 
7.0%
n 863061
 
5.8%
, 827656
 
5.6%
o 732955
 
4.9%
r 621528
 
4.2%
s 543168
 
3.7%
Other values (88) 4920780
33.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 14873592
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1647912
 
11.1%
a 1475775
 
9.9%
t 1110607
 
7.5%
e 1086910
 
7.3%
i 1043240
 
7.0%
n 863061
 
5.8%
, 827656
 
5.6%
o 732955
 
4.9%
r 621528
 
4.2%
s 543168
 
3.7%
Other values (88) 4920780
33.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 14873592
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1647912
 
11.1%
a 1475775
 
9.9%
t 1110607
 
7.5%
e 1086910
 
7.3%
i 1043240
 
7.0%
n 863061
 
5.8%
, 827656
 
5.6%
o 732955
 
4.9%
r 621528
 
4.2%
s 543168
 
3.7%
Other values (88) 4920780
33.1%

continent
Text

Missing 

Distinct65
Distinct (%)< 0.1%
Missing145113
Missing (%)42.8%
Memory size2.6 MiB
2025-03-26T16:19:44.763772image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length50
Median length46
Mean length15.2714038
Min length4

Characters and Unicode

Total characters2959201
Distinct characters35
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowNorth Pacific Ocean
2nd rowSouth Pacific Ocean
3rd rowAsia-Temperate
4th rowNorth Atlantic Ocean
5th rowPacific
ValueCountFrequency (%)
north 94129
21.3%
ocean 69332
15.7%
pacific 66360
15.0%
america 65599
14.8%
atlantic 41429
9.4%
south 31523
 
7.1%
13921
 
3.1%
neotropics 13920
 
3.1%
asia 9249
 
2.1%
africa 8545
 
1.9%
Other values (18) 28407
 
6.4%
2025-03-26T16:19:44.860166image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 337540
11.4%
a 291961
 
9.9%
i 288185
 
9.7%
248640
 
8.4%
t 235723
 
8.0%
r 194655
 
6.6%
e 173565
 
5.9%
o 157657
 
5.3%
n 131625
 
4.4%
A 131466
 
4.4%
Other values (25) 768184
26.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2959201
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
c 337540
11.4%
a 291961
 
9.9%
i 288185
 
9.7%
248640
 
8.4%
t 235723
 
8.0%
r 194655
 
6.6%
e 173565
 
5.9%
o 157657
 
5.3%
n 131625
 
4.4%
A 131466
 
4.4%
Other values (25) 768184
26.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2959201
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
c 337540
11.4%
a 291961
 
9.9%
i 288185
 
9.7%
248640
 
8.4%
t 235723
 
8.0%
r 194655
 
6.6%
e 173565
 
5.9%
o 157657
 
5.3%
n 131625
 
4.4%
A 131466
 
4.4%
Other values (25) 768184
26.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2959201
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
c 337540
11.4%
a 291961
 
9.9%
i 288185
 
9.7%
248640
 
8.4%
t 235723
 
8.0%
r 194655
 
6.6%
e 173565
 
5.9%
o 157657
 
5.3%
n 131625
 
4.4%
A 131466
 
4.4%
Other values (25) 768184
26.0%

waterBody
Text

Missing 

Distinct217
Distinct (%)0.2%
Missing231871
Missing (%)68.4%
Memory size2.6 MiB
2025-03-26T16:19:44.893197image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length69
Median length53
Mean length20.41847014
Min length6

Characters and Unicode

Total characters2185103
Distinct characters55
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique17 ?
Unique (%)< 0.1%

Sample

1st rowNorth Pacific Ocean, Gulf of California
2nd rowSouth Pacific Ocean
3rd rowNorth Atlantic Ocean
4th rowPacific
5th rowNorth Pacific Ocean
ValueCountFrequency (%)
ocean 69333
21.1%
pacific 61730
18.8%
north 47203
14.4%
atlantic 41429
12.6%
south 18448
 
5.6%
sea 18281
 
5.6%
caribbean 14762
 
4.5%
bay 12144
 
3.7%
gulf 7286
 
2.2%
of 6766
 
2.1%
Other values (198) 31269
9.5%
2025-03-26T16:19:45.004070image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 264140
12.1%
c 238219
10.9%
221635
 
10.1%
i 195654
 
9.0%
t 153388
 
7.0%
n 144503
 
6.6%
e 133619
 
6.1%
o 88136
 
4.0%
f 78958
 
3.6%
h 76050
 
3.5%
Other values (45) 590801
27.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2185103
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 264140
12.1%
c 238219
10.9%
221635
 
10.1%
i 195654
 
9.0%
t 153388
 
7.0%
n 144503
 
6.6%
e 133619
 
6.1%
o 88136
 
4.0%
f 78958
 
3.6%
h 76050
 
3.5%
Other values (45) 590801
27.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2185103
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 264140
12.1%
c 238219
10.9%
221635
 
10.1%
i 195654
 
9.0%
t 153388
 
7.0%
n 144503
 
6.6%
e 133619
 
6.1%
o 88136
 
4.0%
f 78958
 
3.6%
h 76050
 
3.5%
Other values (45) 590801
27.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2185103
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 264140
12.1%
c 238219
10.9%
221635
 
10.1%
i 195654
 
9.0%
t 153388
 
7.0%
n 144503
 
6.6%
e 133619
 
6.1%
o 88136
 
4.0%
f 78958
 
3.6%
h 76050
 
3.5%
Other values (45) 590801
27.0%

islandGroup
Text

Missing 

Distinct100
Distinct (%)0.4%
Missing316108
Missing (%)93.3%
Memory size2.6 MiB
2025-03-26T16:19:45.042726image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length24
Median length21
Mean length14.50515826
Min length5

Characters and Unicode

Total characters330413
Distinct characters51
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)< 0.1%

Sample

1st rowSociety Islands
2nd rowLeeward Antilles
3rd rowBahama Islands
4th rowSociety Islands
5th rowVisayas
ValueCountFrequency (%)
islands 15145
31.9%
society 10401
21.9%
leeward 3592
 
7.6%
antilles 3201
 
6.7%
îles 1366
 
2.9%
vent 1366
 
2.9%
du 1305
 
2.7%
cays 1105
 
2.3%
bahama 992
 
2.1%
group 829
 
1.7%
Other values (103) 8225
17.3%
2025-03-26T16:19:45.142619image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 39304
11.9%
a 28873
 
8.7%
e 28114
 
8.5%
24748
 
7.5%
l 24534
 
7.4%
n 22759
 
6.9%
d 21992
 
6.7%
i 17666
 
5.3%
t 16090
 
4.9%
I 15533
 
4.7%
Other values (41) 90800
27.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 330413
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 39304
11.9%
a 28873
 
8.7%
e 28114
 
8.5%
24748
 
7.5%
l 24534
 
7.4%
n 22759
 
6.9%
d 21992
 
6.7%
i 17666
 
5.3%
t 16090
 
4.9%
I 15533
 
4.7%
Other values (41) 90800
27.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 330413
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 39304
11.9%
a 28873
 
8.7%
e 28114
 
8.5%
24748
 
7.5%
l 24534
 
7.4%
n 22759
 
6.9%
d 21992
 
6.7%
i 17666
 
5.3%
t 16090
 
4.9%
I 15533
 
4.7%
Other values (41) 90800
27.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 330413
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 39304
11.9%
a 28873
 
8.7%
e 28114
 
8.5%
24748
 
7.5%
l 24534
 
7.4%
n 22759
 
6.9%
d 21992
 
6.7%
i 17666
 
5.3%
t 16090
 
4.9%
I 15533
 
4.7%
Other values (41) 90800
27.5%

island
Text

Missing 

Distinct566
Distinct (%)1.0%
Missing279899
Missing (%)82.6%
Memory size2.6 MiB
2025-03-26T16:19:45.269200image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length31
Median length25
Mean length8.430782532
Min length3

Characters and Unicode

Total characters497315
Distinct characters62
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)0.1%

Sample

1st rowMoorea
2nd rowMoorea
3rd rowMindanao
4th rowKlein Curacao
5th rowMoorea
ValueCountFrequency (%)
moorea 15986
18.5%
cay 7352
 
8.5%
bow 4792
 
5.5%
carrie 4792
 
5.5%
island 4076
 
4.7%
curacao 3685
 
4.3%
oahu 2252
 
2.6%
luzon 2095
 
2.4%
borneo 2051
 
2.4%
atoll 915
 
1.1%
Other values (560) 38564
44.6%
2025-03-26T16:19:45.459199image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 78719
15.8%
o 63813
12.8%
r 45002
 
9.0%
e 38371
 
7.7%
27572
 
5.5%
u 21126
 
4.2%
n 21014
 
4.2%
i 20882
 
4.2%
C 19961
 
4.0%
M 19741
 
4.0%
Other values (52) 141114
28.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 497315
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 78719
15.8%
o 63813
12.8%
r 45002
 
9.0%
e 38371
 
7.7%
27572
 
5.5%
u 21126
 
4.2%
n 21014
 
4.2%
i 20882
 
4.2%
C 19961
 
4.0%
M 19741
 
4.0%
Other values (52) 141114
28.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 497315
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 78719
15.8%
o 63813
12.8%
r 45002
 
9.0%
e 38371
 
7.7%
27572
 
5.5%
u 21126
 
4.2%
n 21014
 
4.2%
i 20882
 
4.2%
C 19961
 
4.0%
M 19741
 
4.0%
Other values (52) 141114
28.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 497315
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 78719
15.8%
o 63813
12.8%
r 45002
 
9.0%
e 38371
 
7.7%
27572
 
5.5%
u 21126
 
4.2%
n 21014
 
4.2%
i 20882
 
4.2%
C 19961
 
4.0%
M 19741
 
4.0%
Other values (52) 141114
28.4%

country
Text

Missing 

Distinct244
Distinct (%)0.1%
Missing14449
Missing (%)4.3%
Memory size2.6 MiB
2025-03-26T16:19:45.593382image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length44
Median length36
Mean length11.00668849
Min length4

Characters and Unicode

Total characters3570988
Distinct characters66
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)< 0.1%

Sample

1st rowUnited States
2nd rowMexico
3rd rowFrench Polynesia
4th rowUnited States
5th rowChina
ValueCountFrequency (%)
states 151029
28.1%
united 150945
28.1%
french 23185
 
4.3%
polynesia 23003
 
4.3%
mexico 9727
 
1.8%
panama 9234
 
1.7%
belize 9201
 
1.7%
philippines 6792
 
1.3%
guyana 6010
 
1.1%
new 5308
 
1.0%
Other values (266) 142418
26.5%
2025-03-26T16:19:45.803874image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 481153
13.5%
e 435641
12.2%
a 385728
10.8%
i 291453
 
8.2%
n 286608
 
8.0%
212414
 
5.9%
s 206613
 
5.8%
d 173559
 
4.9%
S 162708
 
4.6%
U 152749
 
4.3%
Other values (56) 782362
21.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3570988
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 481153
13.5%
e 435641
12.2%
a 385728
10.8%
i 291453
 
8.2%
n 286608
 
8.0%
212414
 
5.9%
s 206613
 
5.8%
d 173559
 
4.9%
S 162708
 
4.6%
U 152749
 
4.3%
Other values (56) 782362
21.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3570988
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 481153
13.5%
e 435641
12.2%
a 385728
10.8%
i 291453
 
8.2%
n 286608
 
8.0%
212414
 
5.9%
s 206613
 
5.8%
d 173559
 
4.9%
S 162708
 
4.6%
U 152749
 
4.3%
Other values (56) 782362
21.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3570988
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 481153
13.5%
e 435641
12.2%
a 385728
10.8%
i 291453
 
8.2%
n 286608
 
8.0%
212414
 
5.9%
s 206613
 
5.8%
d 173559
 
4.9%
S 162708
 
4.6%
U 152749
 
4.3%
Other values (56) 782362
21.9%

stateProvince
Text

Missing 

Distinct1646
Distinct (%)0.6%
Missing66313
Missing (%)19.6%
Memory size2.6 MiB
2025-03-26T16:19:45.963210image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length52
Median length42
Mean length9.61708747
Min length3

Characters and Unicode

Total characters2621368
Distinct characters82
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique67 ?
Unique (%)< 0.1%

Sample

1st rowArizona
2nd rowArkansas
3rd rowXizang
4th rowLaikipia
5th rowFlorida
ValueCountFrequency (%)
california 17089
 
4.6%
florida 16505
 
4.4%
texas 14347
 
3.9%
virginia 13055
 
3.5%
not 10650
 
2.9%
stated 10650
 
2.9%
arizona 9704
 
2.6%
carolina 8869
 
2.4%
region 8386
 
2.3%
new 8082
 
2.2%
Other values (1667) 254098
68.4%
2025-03-26T16:19:46.177472image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 362258
13.8%
i 257538
 
9.8%
n 192868
 
7.4%
o 191442
 
7.3%
r 175530
 
6.7%
e 143838
 
5.5%
s 117108
 
4.5%
t 109240
 
4.2%
l 104759
 
4.0%
98861
 
3.8%
Other values (72) 867926
33.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2621368
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 362258
13.8%
i 257538
 
9.8%
n 192868
 
7.4%
o 191442
 
7.3%
r 175530
 
6.7%
e 143838
 
5.5%
s 117108
 
4.5%
t 109240
 
4.2%
l 104759
 
4.0%
98861
 
3.8%
Other values (72) 867926
33.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2621368
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 362258
13.8%
i 257538
 
9.8%
n 192868
 
7.4%
o 191442
 
7.3%
r 175530
 
6.7%
e 143838
 
5.5%
s 117108
 
4.5%
t 109240
 
4.2%
l 104759
 
4.0%
98861
 
3.8%
Other values (72) 867926
33.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2621368
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 362258
13.8%
i 257538
 
9.8%
n 192868
 
7.4%
o 191442
 
7.3%
r 175530
 
6.7%
e 143838
 
5.5%
s 117108
 
4.5%
t 109240
 
4.2%
l 104759
 
4.0%
98861
 
3.8%
Other values (72) 867926
33.1%

county
Text

Missing 

Distinct3054
Distinct (%)1.5%
Missing140828
Missing (%)41.6%
Memory size2.6 MiB
2025-03-26T16:19:46.329183image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length56
Median length35
Mean length10.83569542
Min length1

Characters and Unicode

Total characters2146107
Distinct characters83
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique296 ?
Unique (%)0.1%

Sample

1st rowCochise
2nd rowNielamu (Nyalam) Xian
3rd row[Not Stated]
4th row[Not Stated]
5th row[Not Stated]
ValueCountFrequency (%)
not 49730
 
15.0%
stated 49730
 
15.0%
county 38561
 
11.6%
honolulu 5040
 
1.5%
san 4622
 
1.4%
st 3596
 
1.1%
cochise 3345
 
1.0%
lucie 3232
 
1.0%
island 2695
 
0.8%
xian 2354
 
0.7%
Other values (2542) 169322
51.0%
2025-03-26T16:19:46.545631image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 237207
 
11.1%
o 188266
 
8.8%
a 183484
 
8.5%
e 150380
 
7.0%
n 139041
 
6.5%
134168
 
6.3%
u 85424
 
4.0%
i 84752
 
3.9%
d 76779
 
3.6%
r 76459
 
3.6%
Other values (73) 790147
36.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2146107
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 237207
 
11.1%
o 188266
 
8.8%
a 183484
 
8.5%
e 150380
 
7.0%
n 139041
 
6.5%
134168
 
6.3%
u 85424
 
4.0%
i 84752
 
3.9%
d 76779
 
3.6%
r 76459
 
3.6%
Other values (73) 790147
36.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2146107
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 237207
 
11.1%
o 188266
 
8.8%
a 183484
 
8.5%
e 150380
 
7.0%
n 139041
 
6.5%
134168
 
6.3%
u 85424
 
4.0%
i 84752
 
3.9%
d 76779
 
3.6%
r 76459
 
3.6%
Other values (73) 790147
36.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2146107
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 237207
 
11.1%
o 188266
 
8.8%
a 183484
 
8.5%
e 150380
 
7.0%
n 139041
 
6.5%
134168
 
6.3%
u 85424
 
4.0%
i 84752
 
3.9%
d 76779
 
3.6%
r 76459
 
3.6%
Other values (73) 790147
36.8%

locality
Text

Missing 

Distinct31951
Distinct (%)10.5%
Missing34120
Missing (%)10.1%
Memory size2.6 MiB
2025-03-26T16:19:46.691110image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length312
Median length249
Mean length40.82379654
Min length3

Characters and Unicode

Total characters12441746
Distinct characters133
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4473 ?
Unique (%)1.5%

Sample

1st rowCarr Canyon, Huachuca Mountains
2nd rowSociety Islands, Moorea, In front of Hilton
3rd rowAshdown
4th rowNielamu Zhen. Route 318 between Zhangmu and Nielamu (Nyalam) ca. 8 km from Zhangmu.
5th rowMpala Research Centre
ValueCountFrequency (%)
of 95658
 
4.7%
km 27944
 
1.4%
road 26042
 
1.3%
on 20818
 
1.0%
island 19667
 
1.0%
and 19512
 
1.0%
national 18189
 
0.9%
river 17551
 
0.9%
creek 15277
 
0.8%
at 14906
 
0.7%
Other values (27247) 1759888
86.5%
2025-03-26T16:19:46.942860image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1730685
 
13.9%
a 1104843
 
8.9%
e 890558
 
7.2%
o 820923
 
6.6%
n 663377
 
5.3%
i 648704
 
5.2%
r 608740
 
4.9%
t 593452
 
4.8%
l 449999
 
3.6%
s 434446
 
3.5%
Other values (123) 4496019
36.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12441746
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
1730685
 
13.9%
a 1104843
 
8.9%
e 890558
 
7.2%
o 820923
 
6.6%
n 663377
 
5.3%
i 648704
 
5.2%
r 608740
 
4.9%
t 593452
 
4.8%
l 449999
 
3.6%
s 434446
 
3.5%
Other values (123) 4496019
36.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12441746
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
1730685
 
13.9%
a 1104843
 
8.9%
e 890558
 
7.2%
o 820923
 
6.6%
n 663377
 
5.3%
i 648704
 
5.2%
r 608740
 
4.9%
t 593452
 
4.8%
l 449999
 
3.6%
s 434446
 
3.5%
Other values (123) 4496019
36.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12441746
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
1730685
 
13.9%
a 1104843
 
8.9%
e 890558
 
7.2%
o 820923
 
6.6%
n 663377
 
5.3%
i 648704
 
5.2%
r 608740
 
4.9%
t 593452
 
4.8%
l 449999
 
3.6%
s 434446
 
3.5%
Other values (123) 4496019
36.1%
Distinct2610
Distinct (%)2.9%
Missing249580
Missing (%)73.6%
Memory size2.6 MiB
2025-03-26T16:19:47.089417image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.173413058
Min length3

Characters and Unicode

Total characters462022
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique256 ?
Unique (%)0.3%

Sample

1st row1524.0
2nd row2700.0
3rd row1800.0
4th row1000.0
5th row760.0
ValueCountFrequency (%)
5.0 1676
 
1.9%
1100.0 1171
 
1.3%
150.0 1080
 
1.2%
200.0 1049
 
1.2%
1200.0 1002
 
1.1%
50.0 852
 
1.0%
10.0 832
 
0.9%
1829.0 752
 
0.8%
100.0 735
 
0.8%
1487.0 633
 
0.7%
Other values (2597) 79525
89.0%
2025-03-26T16:19:47.301511image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 142539
30.9%
. 89307
19.3%
1 52378
 
11.3%
2 35300
 
7.6%
5 30819
 
6.7%
3 22664
 
4.9%
4 21050
 
4.6%
7 18485
 
4.0%
6 17074
 
3.7%
8 16825
 
3.6%
Other values (2) 15581
 
3.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 462022
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 142539
30.9%
. 89307
19.3%
1 52378
 
11.3%
2 35300
 
7.6%
5 30819
 
6.7%
3 22664
 
4.9%
4 21050
 
4.6%
7 18485
 
4.0%
6 17074
 
3.7%
8 16825
 
3.6%
Other values (2) 15581
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 462022
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 142539
30.9%
. 89307
19.3%
1 52378
 
11.3%
2 35300
 
7.6%
5 30819
 
6.7%
3 22664
 
4.9%
4 21050
 
4.6%
7 18485
 
4.0%
6 17074
 
3.7%
8 16825
 
3.6%
Other values (2) 15581
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 462022
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 142539
30.9%
. 89307
19.3%
1 52378
 
11.3%
2 35300
 
7.6%
5 30819
 
6.7%
3 22664
 
4.9%
4 21050
 
4.6%
7 18485
 
4.0%
6 17074
 
3.7%
8 16825
 
3.6%
Other values (2) 15581
 
3.4%
Distinct1577
Distinct (%)2.9%
Missing285010
Missing (%)84.1%
Memory size2.6 MiB
2025-03-26T16:19:47.459514image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length6
Mean length5.241921414
Min length3

Characters and Unicode

Total characters282419
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique151 ?
Unique (%)0.3%

Sample

1st row1524.0
2nd row1800.0
3rd row1000.0
4th row760.0
5th row650.0
ValueCountFrequency (%)
1200.0 1121
 
2.1%
1100.0 866
 
1.6%
15.0 845
 
1.6%
200.0 771
 
1.4%
1829.0 742
 
1.4%
50.0 644
 
1.2%
1487.0 633
 
1.2%
800.0 616
 
1.1%
1707.0 575
 
1.1%
1800.0 551
 
1.0%
Other values (1564) 46513
86.3%
2025-03-26T16:19:47.681617image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 91439
32.4%
. 53877
19.1%
1 31755
 
11.2%
2 20487
 
7.3%
5 18046
 
6.4%
4 13472
 
4.8%
3 12014
 
4.3%
7 10845
 
3.8%
8 10257
 
3.6%
6 10159
 
3.6%
Other values (2) 10068
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 282419
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 91439
32.4%
. 53877
19.1%
1 31755
 
11.2%
2 20487
 
7.3%
5 18046
 
6.4%
4 13472
 
4.8%
3 12014
 
4.3%
7 10845
 
3.8%
8 10257
 
3.6%
6 10159
 
3.6%
Other values (2) 10068
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 282419
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 91439
32.4%
. 53877
19.1%
1 31755
 
11.2%
2 20487
 
7.3%
5 18046
 
6.4%
4 13472
 
4.8%
3 12014
 
4.3%
7 10845
 
3.8%
8 10257
 
3.6%
6 10159
 
3.6%
Other values (2) 10068
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 282419
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 91439
32.4%
. 53877
19.1%
1 31755
 
11.2%
2 20487
 
7.3%
5 18046
 
6.4%
4 13472
 
4.8%
3 12014
 
4.3%
7 10845
 
3.8%
8 10257
 
3.6%
6 10159
 
3.6%
Other values (2) 10068
 
3.6%

verbatimElevation
Text

Missing 

Distinct913
Distinct (%)5.7%
Missing322925
Missing (%)95.3%
Memory size2.6 MiB
2025-03-26T16:19:47.823178image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length33
Median length27
Mean length6.528379902
Min length1

Characters and Unicode

Total characters104206
Distinct characters47
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique164 ?
Unique (%)1.0%

Sample

1st row760 m
2nd row1050 ft
3rd row611 m
4th row73 m
5th row500 ft
ValueCountFrequency (%)
m 8089
23.4%
ft 7373
21.3%
ca 907
 
2.6%
503
 
1.5%
50 384
 
1.1%
3440 336
 
1.0%
sea 324
 
0.9%
level 324
 
0.9%
54 315
 
0.9%
80 302
 
0.9%
Other values (758) 15692
45.4%
2025-03-26T16:19:48.106123image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
18587
17.8%
0 15831
15.2%
m 8262
 
7.9%
t 7851
 
7.5%
f 7476
 
7.2%
1 5488
 
5.3%
5 4899
 
4.7%
3 4559
 
4.4%
4 4555
 
4.4%
2 4238
 
4.1%
Other values (37) 22460
21.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 104206
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
18587
17.8%
0 15831
15.2%
m 8262
 
7.9%
t 7851
 
7.5%
f 7476
 
7.2%
1 5488
 
5.3%
5 4899
 
4.7%
3 4559
 
4.4%
4 4555
 
4.4%
2 4238
 
4.1%
Other values (37) 22460
21.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 104206
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
18587
17.8%
0 15831
15.2%
m 8262
 
7.9%
t 7851
 
7.5%
f 7476
 
7.2%
1 5488
 
5.3%
5 4899
 
4.7%
3 4559
 
4.4%
4 4555
 
4.4%
2 4238
 
4.1%
Other values (37) 22460
21.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 104206
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
18587
17.8%
0 15831
15.2%
m 8262
 
7.9%
t 7851
 
7.5%
f 7476
 
7.2%
1 5488
 
5.3%
5 4899
 
4.7%
3 4559
 
4.4%
4 4555
 
4.4%
2 4238
 
4.1%
Other values (37) 22460
21.6%

minimumDepthInMeters
Text

Missing 

Distinct2027
Distinct (%)2.7%
Missing264554
Missing (%)78.1%
Memory size2.6 MiB
2025-03-26T16:19:48.146826image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.129296544
Min length3

Characters and Unicode

Total characters306943
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique622 ?
Unique (%)0.8%

Sample

1st row1785.34
2nd row13.0
3rd row0.0
4th row25.0
5th row3456.48
ValueCountFrequency (%)
0.0 13862
 
18.6%
1.0 5906
 
7.9%
3.0 3922
 
5.3%
0.5 2543
 
3.4%
2.0 2376
 
3.2%
10.0 2028
 
2.7%
15.0 1884
 
2.5%
1.5 1341
 
1.8%
12.0 1316
 
1.8%
5.0 1310
 
1.8%
Other values (2011) 37845
50.9%
2025-03-26T16:19:48.241631image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 91894
29.9%
. 74333
24.2%
1 33790
 
11.0%
2 22652
 
7.4%
5 20079
 
6.5%
3 16731
 
5.5%
6 10925
 
3.6%
7 9757
 
3.2%
8 9569
 
3.1%
9 8676
 
2.8%
Other values (2) 8537
 
2.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 306943
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 91894
29.9%
. 74333
24.2%
1 33790
 
11.0%
2 22652
 
7.4%
5 20079
 
6.5%
3 16731
 
5.5%
6 10925
 
3.6%
7 9757
 
3.2%
8 9569
 
3.1%
9 8676
 
2.8%
Other values (2) 8537
 
2.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 306943
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 91894
29.9%
. 74333
24.2%
1 33790
 
11.0%
2 22652
 
7.4%
5 20079
 
6.5%
3 16731
 
5.5%
6 10925
 
3.6%
7 9757
 
3.2%
8 9569
 
3.1%
9 8676
 
2.8%
Other values (2) 8537
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 306943
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 91894
29.9%
. 74333
24.2%
1 33790
 
11.0%
2 22652
 
7.4%
5 20079
 
6.5%
3 16731
 
5.5%
6 10925
 
3.6%
7 9757
 
3.2%
8 9569
 
3.1%
9 8676
 
2.8%
Other values (2) 8537
 
2.8%

maximumDepthInMeters
Text

Missing 

Distinct1922
Distinct (%)2.9%
Missing271546
Missing (%)80.1%
Memory size2.6 MiB
2025-03-26T16:19:48.365791image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.1191102
Min length3

Characters and Unicode

Total characters277385
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique561 ?
Unique (%)0.8%

Sample

1st row1785.34
2nd row17.0
3rd row98.0
4th row35.0
5th row3456.48
ValueCountFrequency (%)
1.0 6746
 
10.0%
3.0 5346
 
7.9%
2.0 3531
 
5.2%
5.0 2503
 
3.7%
0.5 1769
 
2.6%
10.0 1696
 
2.5%
1.5 1510
 
2.2%
20.0 1486
 
2.2%
18.0 1432
 
2.1%
12.0 1155
 
1.7%
Other values (1906) 40167
59.6%
2025-03-26T16:19:48.559840image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 71249
25.7%
. 67341
24.3%
1 34422
12.4%
2 21396
 
7.7%
5 18373
 
6.6%
3 17811
 
6.4%
8 10260
 
3.7%
6 9281
 
3.3%
9 9192
 
3.3%
7 9187
 
3.3%
Other values (2) 8873
 
3.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 277385
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 71249
25.7%
. 67341
24.3%
1 34422
12.4%
2 21396
 
7.7%
5 18373
 
6.6%
3 17811
 
6.4%
8 10260
 
3.7%
6 9281
 
3.3%
9 9192
 
3.3%
7 9187
 
3.3%
Other values (2) 8873
 
3.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 277385
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 71249
25.7%
. 67341
24.3%
1 34422
12.4%
2 21396
 
7.7%
5 18373
 
6.6%
3 17811
 
6.4%
8 10260
 
3.7%
6 9281
 
3.3%
9 9192
 
3.3%
7 9187
 
3.3%
Other values (2) 8873
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 277385
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 71249
25.7%
. 67341
24.3%
1 34422
12.4%
2 21396
 
7.7%
5 18373
 
6.6%
3 17811
 
6.4%
8 10260
 
3.7%
6 9281
 
3.3%
9 9192
 
3.3%
7 9187
 
3.3%
Other values (2) 8873
 
3.2%

verbatimDepth
Text

Missing 

Distinct59
Distinct (%)4.0%
Missing337405
Missing (%)99.6%
Memory size2.6 MiB
2025-03-26T16:19:48.601872image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length91
Median length10
Mean length8.626180837
Min length2

Characters and Unicode

Total characters12784
Distinct characters51
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique29 ?
Unique (%)2.0%

Sample

1st rowto 1 m
2nd rowintertidal
3rd row<0.5 m
4th rowintertidal
5th rowintertidal
ValueCountFrequency (%)
intertidal 780
40.5%
m 259
 
13.5%
surface 254
 
13.2%
to 103
 
5.4%
1 95
 
4.9%
0-1 84
 
4.4%
intertida 84
 
4.4%
0.5 68
 
3.5%
1m 47
 
2.4%
cm 13
 
0.7%
Other values (55) 138
 
7.2%
2025-03-26T16:19:48.697831image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
t 1875
14.7%
i 1384
10.8%
e 1170
9.2%
a 1153
9.0%
r 1150
9.0%
n 893
 
7.0%
d 879
 
6.9%
l 808
 
6.3%
443
 
3.5%
I 353
 
2.8%
Other values (41) 2676
20.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 12784
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
t 1875
14.7%
i 1384
10.8%
e 1170
9.2%
a 1153
9.0%
r 1150
9.0%
n 893
 
7.0%
d 879
 
6.9%
l 808
 
6.3%
443
 
3.5%
I 353
 
2.8%
Other values (41) 2676
20.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 12784
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
t 1875
14.7%
i 1384
10.8%
e 1170
9.2%
a 1153
9.0%
r 1150
9.0%
n 893
 
7.0%
d 879
 
6.9%
l 808
 
6.3%
443
 
3.5%
I 353
 
2.8%
Other values (41) 2676
20.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 12784
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
t 1875
14.7%
i 1384
10.8%
e 1170
9.2%
a 1153
9.0%
r 1150
9.0%
n 893
 
7.0%
d 879
 
6.9%
l 808
 
6.3%
443
 
3.5%
I 353
 
2.8%
Other values (41) 2676
20.9%

decimalLatitude
Text

Missing 

Distinct22667
Distinct (%)8.6%
Missing73966
Missing (%)21.8%
Memory size2.6 MiB
2025-03-26T16:19:48.840393image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length7
Mean length6.754311663
Min length3

Characters and Unicode

Total characters1789359
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3754 ?
Unique (%)1.4%

Sample

1st row31.434
2nd row27.5772
3rd row-17.4756
4th row28.0392
5th row0.293
ValueCountFrequency (%)
12.0832 1370
 
0.5%
16.802 1085
 
0.4%
22.0 898
 
0.3%
31.7306 897
 
0.3%
5.0 793
 
0.3%
17.4726 766
 
0.3%
38.6141 728
 
0.3%
17.4825 684
 
0.3%
34.9606 682
 
0.3%
9.82436 665
 
0.3%
Other values (22422) 256353
96.8%
2025-03-26T16:19:49.055204image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 264921
14.8%
3 225274
12.6%
1 184984
10.3%
2 163113
9.1%
7 157950
8.8%
4 151984
8.5%
8 134617
7.5%
5 129894
7.3%
6 125862
7.0%
9 108155
6.0%
Other values (2) 142605
8.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1789359
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 264921
14.8%
3 225274
12.6%
1 184984
10.3%
2 163113
9.1%
7 157950
8.8%
4 151984
8.5%
8 134617
7.5%
5 129894
7.3%
6 125862
7.0%
9 108155
6.0%
Other values (2) 142605
8.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1789359
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 264921
14.8%
3 225274
12.6%
1 184984
10.3%
2 163113
9.1%
7 157950
8.8%
4 151984
8.5%
8 134617
7.5%
5 129894
7.3%
6 125862
7.0%
9 108155
6.0%
Other values (2) 142605
8.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1789359
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 264921
14.8%
3 225274
12.6%
1 184984
10.3%
2 163113
9.1%
7 157950
8.8%
4 151984
8.5%
8 134617
7.5%
5 129894
7.3%
6 125862
7.0%
9 108155
6.0%
Other values (2) 142605
8.0%

decimalLongitude
Text

Missing 

Distinct21530
Distinct (%)8.1%
Missing73966
Missing (%)21.8%
Memory size2.6 MiB
2025-03-26T16:19:49.207768image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length8
Median length8
Mean length7.488606037
Min length3

Characters and Unicode

Total characters1983889
Distinct characters12
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3512 ?
Unique (%)1.3%

Sample

1st row-110.285
2nd row-111.45
3rd row-149.842
4th row85.9858
5th row36.899
ValueCountFrequency (%)
68.8991 1352
 
0.5%
56.1167 1223
 
0.5%
149.826 1223
 
0.5%
88.082 1101
 
0.4%
149.775 1057
 
0.4%
110.881 915
 
0.3%
88.0817 838
 
0.3%
80.2986 744
 
0.3%
90.2589 733
 
0.3%
176.0 682
 
0.3%
Other values (21346) 255053
96.3%
2025-03-26T16:19:49.417385image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 264921
13.4%
1 242563
12.2%
- 217162
10.9%
8 175553
8.8%
7 174723
8.8%
9 158960
8.0%
6 132764
6.7%
4 129900
6.5%
2 128022
6.5%
5 123405
6.2%
Other values (2) 235916
11.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1983889
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
. 264921
13.4%
1 242563
12.2%
- 217162
10.9%
8 175553
8.8%
7 174723
8.8%
9 158960
8.0%
6 132764
6.7%
4 129900
6.5%
2 128022
6.5%
5 123405
6.2%
Other values (2) 235916
11.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1983889
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
. 264921
13.4%
1 242563
12.2%
- 217162
10.9%
8 175553
8.8%
7 174723
8.8%
9 158960
8.0%
6 132764
6.7%
4 129900
6.5%
2 128022
6.5%
5 123405
6.2%
Other values (2) 235916
11.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1983889
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
. 264921
13.4%
1 242563
12.2%
- 217162
10.9%
8 175553
8.8%
7 174723
8.8%
9 158960
8.0%
6 132764
6.7%
4 129900
6.5%
2 128022
6.5%
5 123405
6.2%
Other values (2) 235916
11.9%

geodeticDatum
Text

Missing 

Distinct11
Distinct (%)< 0.1%
Missing308701
Missing (%)91.1%
Memory size2.6 MiB
2025-03-26T16:19:49.465176image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length28
Median length18
Mean length13.85914
Min length5

Characters and Unicode

Total characters418352
Distinct characters40
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowWGS 84 (EPSG:4326)
2nd rowWGS84
3rd rowWGS 84 (EPSG:4326)
4th rowWGS 84 (EPSG:4326)
5th rowWGS 84 (EPSG:4326)
ValueCountFrequency (%)
wgs 20240
28.5%
84 20240
28.5%
epsg:4326 19979
28.1%
wgs84 7759
 
10.9%
wgs1984 1331
 
1.9%
not 320
 
0.5%
recorded 320
 
0.5%
nad27 243
 
0.3%
nad83 231
 
0.3%
epsg:4269 146
 
0.2%
Other values (6) 172
 
0.2%
2025-03-26T16:19:49.546031image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
G 49479
11.8%
S 49455
11.8%
4 49455
11.8%
40795
9.8%
8 29637
 
7.1%
W 29330
 
7.0%
2 20392
 
4.9%
3 20210
 
4.8%
) 20125
 
4.8%
6 20125
 
4.8%
Other values (30) 89349
21.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 418352
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
G 49479
11.8%
S 49455
11.8%
4 49455
11.8%
40795
9.8%
8 29637
 
7.1%
W 29330
 
7.0%
2 20392
 
4.9%
3 20210
 
4.8%
) 20125
 
4.8%
6 20125
 
4.8%
Other values (30) 89349
21.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 418352
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
G 49479
11.8%
S 49455
11.8%
4 49455
11.8%
40795
9.8%
8 29637
 
7.1%
W 29330
 
7.0%
2 20392
 
4.9%
3 20210
 
4.8%
) 20125
 
4.8%
6 20125
 
4.8%
Other values (30) 89349
21.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 418352
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
G 49479
11.8%
S 49455
11.8%
4 49455
11.8%
40795
9.8%
8 29637
 
7.1%
W 29330
 
7.0%
2 20392
 
4.9%
3 20210
 
4.8%
) 20125
 
4.8%
6 20125
 
4.8%
Other values (30) 89349
21.4%
Distinct453
Distinct (%)4.1%
Missing327845
Missing (%)96.7%
Memory size2.6 MiB
2025-03-26T16:19:49.671493image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length7
Median length6
Mean length3.431081326
Min length1

Characters and Unicode

Total characters37886
Distinct characters11
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)0.4%

Sample

1st row500
2nd row500
3rd row140000
4th row100
5th row100
ValueCountFrequency (%)
100 1574
 
14.3%
5 436
 
3.9%
14 404
 
3.7%
12 386
 
3.5%
500 366
 
3.3%
10 312
 
2.8%
32 277
 
2.5%
200 273
 
2.5%
15 256
 
2.3%
23 231
 
2.1%
Other values (443) 6527
59.1%
2025-03-26T16:19:49.861703image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8151
21.5%
1 6739
17.8%
2 4913
13.0%
5 3567
9.4%
4 3261
8.6%
3 3023
 
8.0%
6 2091
 
5.5%
8 1729
 
4.6%
9 1660
 
4.4%
7 1541
 
4.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 37886
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
0 8151
21.5%
1 6739
17.8%
2 4913
13.0%
5 3567
9.4%
4 3261
8.6%
3 3023
 
8.0%
6 2091
 
5.5%
8 1729
 
4.6%
9 1660
 
4.4%
7 1541
 
4.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 37886
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
0 8151
21.5%
1 6739
17.8%
2 4913
13.0%
5 3567
9.4%
4 3261
8.6%
3 3023
 
8.0%
6 2091
 
5.5%
8 1729
 
4.6%
9 1660
 
4.4%
7 1541
 
4.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 37886
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
0 8151
21.5%
1 6739
17.8%
2 4913
13.0%
5 3567
9.4%
4 3261
8.6%
3 3023
 
8.0%
6 2091
 
5.5%
8 1729
 
4.6%
9 1660
 
4.4%
7 1541
 
4.1%

verbatimLatitude
Text

Missing 

Distinct7620
Distinct (%)7.0%
Missing230356
Missing (%)68.0%
Memory size2.6 MiB
2025-03-26T16:19:50.001530image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length38
Median length29
Mean length9.91026527
Min length1

Characters and Unicode

Total characters1075571
Distinct characters40
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1980 ?
Unique (%)1.8%

Sample

1st row27.57721471
2nd row-17.47564
3rd row27 25.347 N
4th row17 28 57.5 S
5th row36.22739648
ValueCountFrequency (%)
n 36363
 
14.9%
s 13624
 
5.6%
17 3928
 
1.6%
12 3360
 
1.4%
27 3325
 
1.4%
36 3193
 
1.3%
3137
 
1.3%
35 3068
 
1.3%
16 3018
 
1.2%
38 2724
 
1.1%
Other values (6457) 169020
69.1%
2025-03-26T16:19:50.204801image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
136229
12.7%
1 101664
9.5%
3 91144
8.5%
2 86719
 
8.1%
. 84998
 
7.9%
4 79006
 
7.3%
7 73774
 
6.9%
0 73676
 
6.8%
5 70453
 
6.6%
8 60080
 
5.6%
Other values (30) 217828
20.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1075571
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
136229
12.7%
1 101664
9.5%
3 91144
8.5%
2 86719
 
8.1%
. 84998
 
7.9%
4 79006
 
7.3%
7 73774
 
6.9%
0 73676
 
6.8%
5 70453
 
6.6%
8 60080
 
5.6%
Other values (30) 217828
20.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1075571
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
136229
12.7%
1 101664
9.5%
3 91144
8.5%
2 86719
 
8.1%
. 84998
 
7.9%
4 79006
 
7.3%
7 73774
 
6.9%
0 73676
 
6.8%
5 70453
 
6.6%
8 60080
 
5.6%
Other values (30) 217828
20.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1075571
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
136229
12.7%
1 101664
9.5%
3 91144
8.5%
2 86719
 
8.1%
. 84998
 
7.9%
4 79006
 
7.3%
7 73774
 
6.9%
0 73676
 
6.8%
5 70453
 
6.6%
8 60080
 
5.6%
Other values (30) 217828
20.3%

verbatimLongitude
Text

Missing 

Distinct7633
Distinct (%)7.0%
Missing230383
Missing (%)68.0%
Memory size2.6 MiB
2025-03-26T16:19:50.339102image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length255
Median length32
Mean length10.73488535
Min length2

Characters and Unicode

Total characters1164778
Distinct characters41
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1959 ?
Unique (%)1.8%

Sample

1st row-111.4495292
2nd row-149.84247
3rd row79 56.156 W
4th row149 53 59.6 W
5th row-122.879564
ValueCountFrequency (%)
w 38553
 
15.8%
e 11410
 
4.7%
3091
 
1.3%
149 2727
 
1.1%
53 2151
 
0.9%
68 1812
 
0.7%
075 1722
 
0.7%
79 1634
 
0.7%
55 1504
 
0.6%
77 1464
 
0.6%
Other values (6617) 178466
73.0%
2025-03-26T16:19:50.527342image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
136030
11.7%
1 113108
9.7%
0 89845
 
7.7%
8 85886
 
7.4%
. 84963
 
7.3%
5 83445
 
7.2%
7 79513
 
6.8%
2 77729
 
6.7%
4 77051
 
6.6%
9 74018
 
6.4%
Other values (31) 263190
22.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1164778
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
136030
11.7%
1 113108
9.7%
0 89845
 
7.7%
8 85886
 
7.4%
. 84963
 
7.3%
5 83445
 
7.2%
7 79513
 
6.8%
2 77729
 
6.7%
4 77051
 
6.6%
9 74018
 
6.4%
Other values (31) 263190
22.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1164778
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
136030
11.7%
1 113108
9.7%
0 89845
 
7.7%
8 85886
 
7.4%
. 84963
 
7.3%
5 83445
 
7.2%
7 79513
 
6.8%
2 77729
 
6.7%
4 77051
 
6.6%
9 74018
 
6.4%
Other values (31) 263190
22.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1164778
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
136030
11.7%
1 113108
9.7%
0 89845
 
7.7%
8 85886
 
7.4%
. 84963
 
7.3%
5 83445
 
7.2%
7 79513
 
6.8%
2 77729
 
6.7%
4 77051
 
6.6%
9 74018
 
6.4%
Other values (31) 263190
22.6%
Distinct6
Distinct (%)0.1%
Missing329806
Missing (%)97.3%
Memory size2.6 MiB
2025-03-26T16:19:50.564898image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length23
Mean length22.74683405
Min length3

Characters and Unicode

Total characters206564
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDegrees Minutes Seconds
2nd rowDegrees Minutes Seconds
3rd rowDegrees Minutes Seconds
4th rowDegrees Minutes Seconds
5th rowDegrees Minutes Seconds
ValueCountFrequency (%)
degrees 8934
33.1%
minutes 8859
32.8%
seconds 8859
32.8%
township 107
 
0.4%
range 107
 
0.4%
decimal 75
 
0.3%
utm 24
 
0.1%
unknown 16
 
0.1%
2025-03-26T16:19:50.655180image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 44702
21.6%
s 26759
13.0%
n 17980
 
8.7%
17900
 
8.7%
g 9041
 
4.4%
i 9041
 
4.4%
D 8998
 
4.4%
o 8982
 
4.3%
c 8934
 
4.3%
r 8934
 
4.3%
Other values (15) 45293
21.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 206564
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 44702
21.6%
s 26759
13.0%
n 17980
 
8.7%
17900
 
8.7%
g 9041
 
4.4%
i 9041
 
4.4%
D 8998
 
4.4%
o 8982
 
4.3%
c 8934
 
4.3%
r 8934
 
4.3%
Other values (15) 45293
21.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 206564
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 44702
21.6%
s 26759
13.0%
n 17980
 
8.7%
17900
 
8.7%
g 9041
 
4.4%
i 9041
 
4.4%
D 8998
 
4.4%
o 8982
 
4.3%
c 8934
 
4.3%
r 8934
 
4.3%
Other values (15) 45293
21.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 206564
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 44702
21.6%
s 26759
13.0%
n 17980
 
8.7%
17900
 
8.7%
g 9041
 
4.4%
i 9041
 
4.4%
D 8998
 
4.4%
o 8982
 
4.3%
c 8934
 
4.3%
r 8934
 
4.3%
Other values (15) 45293
21.9%

georeferenceProtocol
Text

Missing 

Distinct172
Distinct (%)0.2%
Missing255857
Missing (%)75.5%
Memory size2.6 MiB
2025-03-26T16:19:50.685521image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length228
Median length12
Mean length16.01193545
Min length3

Characters and Unicode

Total characters1329471
Distinct characters69
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)< 0.1%

Sample

1st rowGoogle Earth
2nd rowGoogle Earth
3rd rowGoogle Earth
4th rowGeoLocate
5th rowGoogle Earth
ValueCountFrequency (%)
google 50810
24.4%
earth 44802
21.5%
gps 24234
 
11.6%
maps 6435
 
3.1%
georeferencing 5009
 
2.4%
and 3632
 
1.7%
pro 3259
 
1.6%
for 3186
 
1.5%
to 3186
 
1.5%
best 3185
 
1.5%
Other values (336) 60653
29.1%
2025-03-26T16:19:50.784504image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 140235
 
10.5%
125361
 
9.4%
e 117126
 
8.8%
r 92089
 
6.9%
G 90512
 
6.8%
a 87035
 
6.5%
t 73154
 
5.5%
g 60429
 
4.5%
l 58440
 
4.4%
h 52575
 
4.0%
Other values (59) 432515
32.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1329471
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 140235
 
10.5%
125361
 
9.4%
e 117126
 
8.8%
r 92089
 
6.9%
G 90512
 
6.8%
a 87035
 
6.5%
t 73154
 
5.5%
g 60429
 
4.5%
l 58440
 
4.4%
h 52575
 
4.0%
Other values (59) 432515
32.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1329471
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 140235
 
10.5%
125361
 
9.4%
e 117126
 
8.8%
r 92089
 
6.9%
G 90512
 
6.8%
a 87035
 
6.5%
t 73154
 
5.5%
g 60429
 
4.5%
l 58440
 
4.4%
h 52575
 
4.0%
Other values (59) 432515
32.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1329471
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 140235
 
10.5%
125361
 
9.4%
e 117126
 
8.8%
r 92089
 
6.9%
G 90512
 
6.8%
a 87035
 
6.5%
t 73154
 
5.5%
g 60429
 
4.5%
l 58440
 
4.4%
h 52575
 
4.0%
Other values (59) 432515
32.5%

georeferenceRemarks
Text

Missing 

Distinct224
Distinct (%)2.4%
Missing329359
Missing (%)97.2%
Memory size2.6 MiB
2025-03-26T16:19:50.827634image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length83
Median length51
Mean length18.52896725
Min length2

Characters and Unicode

Total characters176544
Distinct characters63
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)0.2%

Sample

1st rowMax error (m): 100
2nd rowMax error (m): 40
3rd rowLocality extent = 1.6
4th rowLocality extent = 1 mile
5th rowMax error (m): 200
ValueCountFrequency (%)
m 5368
14.5%
max 4980
13.5%
error 4980
13.5%
1997
 
5.4%
locality 1825
 
4.9%
extent 1824
 
4.9%
100 1769
 
4.8%
50 918
 
2.5%
200 740
 
2.0%
4 671
 
1.8%
Other values (241) 11855
32.1%
2025-03-26T16:19:50.942355image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
27399
15.5%
r 16719
 
9.5%
e 10676
 
6.0%
o 10254
 
5.8%
a 10145
 
5.7%
t 9638
 
5.5%
0 8357
 
4.7%
x 7022
 
4.0%
m 6554
 
3.7%
n 5392
 
3.1%
Other values (53) 64388
36.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 176544
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
27399
15.5%
r 16719
 
9.5%
e 10676
 
6.0%
o 10254
 
5.8%
a 10145
 
5.7%
t 9638
 
5.5%
0 8357
 
4.7%
x 7022
 
4.0%
m 6554
 
3.7%
n 5392
 
3.1%
Other values (53) 64388
36.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 176544
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
27399
15.5%
r 16719
 
9.5%
e 10676
 
6.0%
o 10254
 
5.8%
a 10145
 
5.7%
t 9638
 
5.5%
0 8357
 
4.7%
x 7022
 
4.0%
m 6554
 
3.7%
n 5392
 
3.1%
Other values (53) 64388
36.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 176544
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
27399
15.5%
r 16719
 
9.5%
e 10676
 
6.0%
o 10254
 
5.8%
a 10145
 
5.7%
t 9638
 
5.5%
0 8357
 
4.7%
x 7022
 
4.0%
m 6554
 
3.7%
n 5392
 
3.1%
Other values (53) 64388
36.5%
Distinct16
Distinct (%)0.3%
Missing333807
Missing (%)98.5%
Memory size2.6 MiB
2025-03-26T16:19:50.974406image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length9
Median length8
Mean length5.252165354
Min length2

Characters and Unicode

Total characters26681
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowaff.
2nd rowcf.
3rd rowaff.
4th rowuncertain
5th rowuncertain
ValueCountFrequency (%)
cf 2749
53.9%
uncertain 1860
36.5%
aff 320
 
6.3%
near 75
 
1.5%
complex 38
 
0.7%
sp 16
 
0.3%
group 12
 
0.2%
n 10
 
0.2%
nov 6
 
0.1%
s.l 6
 
0.1%
Other values (2) 9
 
0.2%
2025-03-26T16:19:51.061661image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
c 4641
17.4%
n 3811
14.3%
f 3389
12.7%
. 2741
10.3%
a 2239
8.4%
e 1978
7.4%
r 1947
7.3%
t 1860
7.0%
i 1860
7.0%
u 1844
 
6.9%
Other values (12) 371
 
1.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 26681
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
c 4641
17.4%
n 3811
14.3%
f 3389
12.7%
. 2741
10.3%
a 2239
8.4%
e 1978
7.4%
r 1947
7.3%
t 1860
7.0%
i 1860
7.0%
u 1844
 
6.9%
Other values (12) 371
 
1.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 26681
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
c 4641
17.4%
n 3811
14.3%
f 3389
12.7%
. 2741
10.3%
a 2239
8.4%
e 1978
7.4%
r 1947
7.3%
t 1860
7.0%
i 1860
7.0%
u 1844
 
6.9%
Other values (12) 371
 
1.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 26681
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
c 4641
17.4%
n 3811
14.3%
f 3389
12.7%
. 2741
10.3%
a 2239
8.4%
e 1978
7.4%
r 1947
7.3%
t 1860
7.0%
i 1860
7.0%
u 1844
 
6.9%
Other values (12) 371
 
1.4%

typeStatus
Text

Missing 

Distinct33
Distinct (%)0.5%
Missing332270
Missing (%)98.0%
Memory size2.6 MiB
2025-03-26T16:19:51.089350image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length27
Median length8
Mean length8.101254345
Min length2

Characters and Unicode

Total characters53606
Distinct characters39
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st rowParatype
2nd rowParatype
3rd rowParatype
4th rowParatype
5th rowParatype
ValueCountFrequency (%)
paratype 5811
86.8%
holotype 332
 
5.0%
paralectotype 125
 
1.9%
cotype 86
 
1.3%
syntype 78
 
1.2%
type 73
 
1.1%
of 34
 
0.5%
paratopotype 33
 
0.5%
allotype 23
 
0.3%
ms 22
 
0.3%
Other values (22) 80
 
1.2%
2025-03-26T16:19:51.181374image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 12008
22.4%
e 6781
12.6%
t 6721
12.5%
y 6683
12.5%
p 6675
12.5%
r 5996
11.2%
P 5973
11.1%
o 1043
 
1.9%
l 522
 
1.0%
H 338
 
0.6%
Other values (29) 866
 
1.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 53606
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 12008
22.4%
e 6781
12.6%
t 6721
12.5%
y 6683
12.5%
p 6675
12.5%
r 5996
11.2%
P 5973
11.1%
o 1043
 
1.9%
l 522
 
1.0%
H 338
 
0.6%
Other values (29) 866
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 53606
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 12008
22.4%
e 6781
12.6%
t 6721
12.5%
y 6683
12.5%
p 6675
12.5%
r 5996
11.2%
P 5973
11.1%
o 1043
 
1.9%
l 522
 
1.0%
H 338
 
0.6%
Other values (29) 866
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 53606
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 12008
22.4%
e 6781
12.6%
t 6721
12.5%
y 6683
12.5%
p 6675
12.5%
r 5996
11.2%
P 5973
11.1%
o 1043
 
1.9%
l 522
 
1.0%
H 338
 
0.6%
Other values (29) 866
 
1.6%

identifiedBy
Text

Missing 

Distinct1867
Distinct (%)1.7%
Missing226576
Missing (%)66.9%
Memory size2.6 MiB
2025-03-26T16:19:51.307671image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length150
Median length128
Mean length39.12351417
Min length2

Characters and Unicode

Total characters4394001
Distinct characters83
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique200 ?
Unique (%)0.2%

Sample

1st rowAnker, Arthur
2nd rowOsborn, Karen J., (IZ), Smithsonian Institution - National Museum of Natural History (UNITED STATES)
3rd rowBaldwin, Carole C.
4th rowHobbs, Horton H., Jr., Smithsonian Institution, National Museum of Natural History
5th rowPaulay, Gustav, University of Florida (UNITED STATES)
ValueCountFrequency (%)
united 36112
 
5.8%
states 36069
 
5.8%
of 27897
 
4.5%
smithsonian 24396
 
3.9%
22526
 
3.6%
institution 20558
 
3.3%
national 18702
 
3.0%
museum 17561
 
2.8%
natural 17279
 
2.8%
history 17200
 
2.8%
Other values (2280) 385078
61.8%
2025-03-26T16:19:51.524213image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
511067
 
11.6%
i 263601
 
6.0%
a 260559
 
5.9%
t 237204
 
5.4%
n 237103
 
5.4%
o 218098
 
5.0%
e 199621
 
4.5%
, 179573
 
4.1%
r 173713
 
4.0%
s 169974
 
3.9%
Other values (73) 1943488
44.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4394001
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
511067
 
11.6%
i 263601
 
6.0%
a 260559
 
5.9%
t 237204
 
5.4%
n 237103
 
5.4%
o 218098
 
5.0%
e 199621
 
4.5%
, 179573
 
4.1%
r 173713
 
4.0%
s 169974
 
3.9%
Other values (73) 1943488
44.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4394001
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
511067
 
11.6%
i 263601
 
6.0%
a 260559
 
5.9%
t 237204
 
5.4%
n 237103
 
5.4%
o 218098
 
5.0%
e 199621
 
4.5%
, 179573
 
4.1%
r 173713
 
4.0%
s 169974
 
3.9%
Other values (73) 1943488
44.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4394001
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
511067
 
11.6%
i 263601
 
6.0%
a 260559
 
5.9%
t 237204
 
5.4%
n 237103
 
5.4%
o 218098
 
5.0%
e 199621
 
4.5%
, 179573
 
4.1%
r 173713
 
4.0%
s 169974
 
3.9%
Other values (73) 1943488
44.2%

scientificName
Text

Missing 

Distinct46039
Distinct (%)14.6%
Missing24073
Missing (%)7.1%
Memory size2.6 MiB
2025-03-26T16:19:51.775580image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length85
Median length63
Mean length18.57520631
Min length3

Characters and Unicode

Total characters5847735
Distinct characters79
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10046 ?
Unique (%)3.2%

Sample

1st rowRectiostoma fernaldella
2nd rowPolystichum sp.
3rd rowMesontoplatys bolzi
4th rowBursa granularis
5th rowAmanses scopas
ValueCountFrequency (%)
sp 50752
 
7.9%
plethodon 4681
 
0.7%
orconectes 4561
 
0.7%
indet 4212
 
0.7%
procambarus 3795
 
0.6%
unidentified 3708
 
0.6%
bathymodiolus 2604
 
0.4%
cinereus 2332
 
0.4%
riftia 2011
 
0.3%
truncatus 1931
 
0.3%
Other values (42997) 558271
87.4%
2025-03-26T16:19:52.010633image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 628771
 
10.8%
i 495090
 
8.5%
s 466610
 
8.0%
e 412819
 
7.1%
o 370672
 
6.3%
r 353257
 
6.0%
324044
 
5.5%
l 300711
 
5.1%
n 295711
 
5.1%
t 291798
 
5.0%
Other values (69) 1908252
32.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 5847735
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 628771
 
10.8%
i 495090
 
8.5%
s 466610
 
8.0%
e 412819
 
7.1%
o 370672
 
6.3%
r 353257
 
6.0%
324044
 
5.5%
l 300711
 
5.1%
n 295711
 
5.1%
t 291798
 
5.0%
Other values (69) 1908252
32.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 5847735
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 628771
 
10.8%
i 495090
 
8.5%
s 466610
 
8.0%
e 412819
 
7.1%
o 370672
 
6.3%
r 353257
 
6.0%
324044
 
5.5%
l 300711
 
5.1%
n 295711
 
5.1%
t 291798
 
5.0%
Other values (69) 1908252
32.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 5847735
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 628771
 
10.8%
i 495090
 
8.5%
s 466610
 
8.0%
e 412819
 
7.1%
o 370672
 
6.3%
r 353257
 
6.0%
324044
 
5.5%
l 300711
 
5.1%
n 295711
 
5.1%
t 291798
 
5.0%
Other values (69) 1908252
32.6%

higherClassification
Text

Missing 

Distinct4815
Distinct (%)1.4%
Missing5896
Missing (%)1.7%
Memory size2.6 MiB
2025-03-26T16:19:52.162244image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length162
Median length142
Mean length76.56003315
Min length6

Characters and Unicode

Total characters25493802
Distinct characters68
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique457 ?
Unique (%)0.1%

Sample

1st rowAnimalia, Arthropoda, Insecta, Lepidoptera, Depressariidae, Stenomatinae
2nd rowAnimalia, Annelida, Polychaeta, Sedentaria, Canalipalpata, Sabellida, Siboglinidae
3rd rowAnimalia, Annelida, Polychaeta, Errantia, Amphinomida, Amphinomidae
4th rowAnimalia, Arthropoda, Crustacea, Malacostraca, Eumalacostraca, Eucarida, Decapoda, Pleocyemata, Cambaridae
5th rowPlantae, Pteridophyte, Polypodiales, Dryopteridaceae
ValueCountFrequency (%)
animalia 288095
 
13.0%
arthropoda 146049
 
6.6%
insecta 113363
 
5.1%
chordata 103703
 
4.7%
vertebrata 102661
 
4.6%
lepidoptera 79862
 
3.6%
actinopterygii 40807
 
1.8%
osteichthyes 40805
 
1.8%
neopterygii 40802
 
1.8%
plantae 35597
 
1.6%
Other values (5328) 1222870
55.2%
2025-03-26T16:19:52.393219image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3316965
13.0%
i 2174316
 
8.5%
e 2156792
 
8.5%
1881623
 
7.4%
, 1879344
 
7.4%
t 1542148
 
6.0%
r 1528841
 
6.0%
o 1484819
 
5.8%
n 1003068
 
3.9%
d 935661
 
3.7%
Other values (58) 7590225
29.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 25493802
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 3316965
13.0%
i 2174316
 
8.5%
e 2156792
 
8.5%
1881623
 
7.4%
, 1879344
 
7.4%
t 1542148
 
6.0%
r 1528841
 
6.0%
o 1484819
 
5.8%
n 1003068
 
3.9%
d 935661
 
3.7%
Other values (58) 7590225
29.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 25493802
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 3316965
13.0%
i 2174316
 
8.5%
e 2156792
 
8.5%
1881623
 
7.4%
, 1879344
 
7.4%
t 1542148
 
6.0%
r 1528841
 
6.0%
o 1484819
 
5.8%
n 1003068
 
3.9%
d 935661
 
3.7%
Other values (58) 7590225
29.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 25493802
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 3316965
13.0%
i 2174316
 
8.5%
e 2156792
 
8.5%
1881623
 
7.4%
, 1879344
 
7.4%
t 1542148
 
6.0%
r 1528841
 
6.0%
o 1484819
 
5.8%
n 1003068
 
3.9%
d 935661
 
3.7%
Other values (58) 7590225
29.8%

kingdom
Text

Missing 

Distinct10
Distinct (%)< 0.1%
Missing10617
Missing (%)3.1%
Memory size2.6 MiB
2025-03-26T16:19:52.436105image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length8
Mean length7.904825296
Min length5

Characters and Unicode

Total characters2594917
Distinct characters25
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAnimalia
2nd rowAnimalia
3rd rowAnimalia
4th rowAnimalia
5th rowPlantae
ValueCountFrequency (%)
animalia 288095
87.8%
plantae 35597
 
10.8%
chromista 2998
 
0.9%
eubacteria 1164
 
0.4%
fungi 323
 
0.1%
protista 42
 
< 0.1%
metazoa 24
 
< 0.1%
eukaryota 21
 
< 0.1%
bacteria 3
 
< 0.1%
protozoa 3
 
< 0.1%
2025-03-26T16:19:52.517689image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 652851
25.2%
i 580720
22.4%
n 324015
12.5%
l 323692
12.5%
m 291093
11.2%
A 288095
11.1%
t 39894
 
1.5%
e 36788
 
1.4%
P 35642
 
1.4%
r 4231
 
0.2%
Other values (15) 17896
 
0.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2594917
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 652851
25.2%
i 580720
22.4%
n 324015
12.5%
l 323692
12.5%
m 291093
11.2%
A 288095
11.1%
t 39894
 
1.5%
e 36788
 
1.4%
P 35642
 
1.4%
r 4231
 
0.2%
Other values (15) 17896
 
0.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2594917
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 652851
25.2%
i 580720
22.4%
n 324015
12.5%
l 323692
12.5%
m 291093
11.2%
A 288095
11.1%
t 39894
 
1.5%
e 36788
 
1.4%
P 35642
 
1.4%
r 4231
 
0.2%
Other values (15) 17896
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2594917
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 652851
25.2%
i 580720
22.4%
n 324015
12.5%
l 323692
12.5%
m 291093
11.2%
A 288095
11.1%
t 39894
 
1.5%
e 36788
 
1.4%
P 35642
 
1.4%
r 4231
 
0.2%
Other values (15) 17896
 
0.7%

phylum
Text

Missing 

Distinct62
Distinct (%)< 0.1%
Missing36783
Missing (%)10.9%
Memory size2.6 MiB
2025-03-26T16:19:52.546327image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length33
Median length25
Mean length9.088393401
Min length6

Characters and Unicode

Total characters2745640
Distinct characters46
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)< 0.1%

Sample

1st rowArthropoda
2nd rowAnnelida
3rd rowAnnelida
4th rowArthropoda
5th rowArthropoda
ValueCountFrequency (%)
arthropoda 146049
48.3%
chordata 103703
34.3%
mollusca 20784
 
6.9%
annelida 11363
 
3.8%
cnidaria 3183
 
1.1%
rhodophyta 2945
 
1.0%
miozoa 2076
 
0.7%
echinodermata 1635
 
0.5%
chlorophyta 1623
 
0.5%
porifera 1252
 
0.4%
Other values (60) 8042
 
2.7%
2025-03-26T16:19:52.637149image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 439399
16.0%
a 414722
15.1%
r 409948
14.9%
d 270352
9.8%
h 265234
9.7%
t 263503
9.6%
A 157468
 
5.7%
p 152508
 
5.6%
C 109896
 
4.0%
l 56916
 
2.1%
Other values (36) 205694
7.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2745640
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 439399
16.0%
a 414722
15.1%
r 409948
14.9%
d 270352
9.8%
h 265234
9.7%
t 263503
9.6%
A 157468
 
5.7%
p 152508
 
5.6%
C 109896
 
4.0%
l 56916
 
2.1%
Other values (36) 205694
7.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2745640
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 439399
16.0%
a 414722
15.1%
r 409948
14.9%
d 270352
9.8%
h 265234
9.7%
t 263503
9.6%
A 157468
 
5.7%
p 152508
 
5.6%
C 109896
 
4.0%
l 56916
 
2.1%
Other values (36) 205694
7.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2745640
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 439399
16.0%
a 414722
15.1%
r 409948
14.9%
d 270352
9.8%
h 265234
9.7%
t 263503
9.6%
A 157468
 
5.7%
p 152508
 
5.6%
C 109896
 
4.0%
l 56916
 
2.1%
Other values (36) 205694
7.5%

class
Text

Missing 

Distinct112
Distinct (%)< 0.1%
Missing12524
Missing (%)3.7%
Memory size2.6 MiB
2025-03-26T16:19:52.669319image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length19
Mean length9.506414636
Min length4

Characters and Unicode

Total characters3102542
Distinct characters48
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)< 0.1%

Sample

1st rowInsecta
2nd rowPolychaeta
3rd rowPolychaeta
4th rowMalacostraca
5th rowPteridophyte
ValueCountFrequency (%)
insecta 113363
34.7%
actinopterygii 40807
 
12.5%
malacostraca 27980
 
8.6%
mammalia 24541
 
7.5%
amphibia 18431
 
5.6%
dicotyledonae 15898
 
4.9%
monocotyledonae 10893
 
3.3%
polychaeta 10719
 
3.3%
reptilia 9890
 
3.0%
bivalvia 9788
 
3.0%
Other values (102) 44744
 
13.7%
2025-03-26T16:19:52.769223image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 447063
14.4%
t 292879
 
9.4%
e 268085
 
8.6%
c 260584
 
8.4%
i 258727
 
8.3%
o 207781
 
6.7%
n 201080
 
6.5%
s 163864
 
5.3%
l 122829
 
4.0%
I 113379
 
3.7%
Other values (38) 766271
24.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3102542
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 447063
14.4%
t 292879
 
9.4%
e 268085
 
8.6%
c 260584
 
8.4%
i 258727
 
8.3%
o 207781
 
6.7%
n 201080
 
6.5%
s 163864
 
5.3%
l 122829
 
4.0%
I 113379
 
3.7%
Other values (38) 766271
24.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3102542
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 447063
14.4%
t 292879
 
9.4%
e 268085
 
8.6%
c 260584
 
8.4%
i 258727
 
8.3%
o 207781
 
6.7%
n 201080
 
6.5%
s 163864
 
5.3%
l 122829
 
4.0%
I 113379
 
3.7%
Other values (38) 766271
24.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3102542
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 447063
14.4%
t 292879
 
9.4%
e 268085
 
8.6%
c 260584
 
8.4%
i 258727
 
8.3%
o 207781
 
6.7%
n 201080
 
6.5%
s 163864
 
5.3%
l 122829
 
4.0%
I 113379
 
3.7%
Other values (38) 766271
24.7%

order
Text

Missing 

Distinct532
Distinct (%)0.2%
Missing30456
Missing (%)9.0%
Memory size2.6 MiB
2025-03-26T16:19:52.903294image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length28
Median length22
Mean length9.884628977
Min length5

Characters and Unicode

Total characters3048726
Distinct characters54
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)< 0.1%

Sample

1st rowLepidoptera
2nd rowSabellida
3rd rowAmphinomida
4th rowDecapoda
5th rowPolypodiales
ValueCountFrequency (%)
lepidoptera 79862
25.9%
perciformes 26069
 
8.5%
decapoda 23869
 
7.7%
coleoptera 10165
 
3.3%
anura 10039
 
3.3%
squamata 9587
 
3.1%
hymenoptera 8506
 
2.8%
rodentia 8426
 
2.7%
caudata 8220
 
2.7%
poales 7870
 
2.6%
Other values (523) 115863
37.6%
2025-03-26T16:19:53.105875image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 430110
14.1%
a 378053
12.4%
o 262685
 
8.6%
r 256166
 
8.4%
p 249356
 
8.2%
i 218739
 
7.2%
t 178489
 
5.9%
d 158293
 
5.2%
s 111052
 
3.6%
l 90467
 
3.0%
Other values (44) 715316
23.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3048726
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 430110
14.1%
a 378053
12.4%
o 262685
 
8.6%
r 256166
 
8.4%
p 249356
 
8.2%
i 218739
 
7.2%
t 178489
 
5.9%
d 158293
 
5.2%
s 111052
 
3.6%
l 90467
 
3.0%
Other values (44) 715316
23.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3048726
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 430110
14.1%
a 378053
12.4%
o 262685
 
8.6%
r 256166
 
8.4%
p 249356
 
8.2%
i 218739
 
7.2%
t 178489
 
5.9%
d 158293
 
5.2%
s 111052
 
3.6%
l 90467
 
3.0%
Other values (44) 715316
23.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3048726
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 430110
14.1%
a 378053
12.4%
o 262685
 
8.6%
r 256166
 
8.4%
p 249356
 
8.2%
i 218739
 
7.2%
t 178489
 
5.9%
d 158293
 
5.2%
s 111052
 
3.6%
l 90467
 
3.0%
Other values (44) 715316
23.5%

family
Text

Missing 

Distinct2911
Distinct (%)0.9%
Missing18617
Missing (%)5.5%
Memory size2.6 MiB
2025-03-26T16:19:53.214164image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length38
Median length19
Mean length10.80815874
Min length6

Characters and Unicode

Total characters3461529
Distinct characters62
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique283 ?
Unique (%)0.1%

Sample

1st rowDepressariidae
2nd rowSiboglinidae
3rd rowAmphinomidae
4th rowCambaridae
5th rowDryopteridaceae
ValueCountFrequency (%)
cambaridae 12199
 
3.8%
geometridae 12045
 
3.8%
noctuidae 7960
 
2.5%
tortricidae 7269
 
2.3%
plethodontidae 6797
 
2.1%
poaceae 6695
 
2.1%
delphinidae 5553
 
1.7%
pyralidae 5235
 
1.6%
siboglinidae 5028
 
1.6%
vesicomyidae 4926
 
1.5%
Other values (2904) 246598
77.0%
2025-03-26T16:19:53.386535image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 525117
15.2%
a 509192
14.7%
i 444702
12.8%
d 314133
 
9.1%
r 190651
 
5.5%
o 187598
 
5.4%
c 141996
 
4.1%
t 127944
 
3.7%
l 120794
 
3.5%
n 111396
 
3.2%
Other values (52) 788006
22.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 3461529
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 525117
15.2%
a 509192
14.7%
i 444702
12.8%
d 314133
 
9.1%
r 190651
 
5.5%
o 187598
 
5.4%
c 141996
 
4.1%
t 127944
 
3.7%
l 120794
 
3.5%
n 111396
 
3.2%
Other values (52) 788006
22.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 3461529
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 525117
15.2%
a 509192
14.7%
i 444702
12.8%
d 314133
 
9.1%
r 190651
 
5.5%
o 187598
 
5.4%
c 141996
 
4.1%
t 127944
 
3.7%
l 120794
 
3.5%
n 111396
 
3.2%
Other values (52) 788006
22.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 3461529
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 525117
15.2%
a 509192
14.7%
i 444702
12.8%
d 314133
 
9.1%
r 190651
 
5.5%
o 187598
 
5.4%
c 141996
 
4.1%
t 127944
 
3.7%
l 120794
 
3.5%
n 111396
 
3.2%
Other values (52) 788006
22.8%

genus
Text

Missing 

Distinct19361
Distinct (%)6.2%
Missing25842
Missing (%)7.6%
Memory size2.6 MiB
2025-03-26T16:19:53.533548image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length18
Mean length9.340260985
Min length2

Characters and Unicode

Total characters2923922
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2068 ?
Unique (%)0.7%

Sample

1st rowRectiostoma
2nd rowPolystichum
3rd rowMesontoplatys
4th rowBursa
5th rowAmanses
ValueCountFrequency (%)
plethodon 4679
 
1.5%
orconectes 4561
 
1.5%
indet 4244
 
1.4%
procambarus 3792
 
1.2%
unidentified 3708
 
1.2%
bathymodiolus 2604
 
0.8%
riftia 2011
 
0.6%
tursiops 1924
 
0.6%
cambarus 1854
 
0.6%
delphinus 1667
 
0.5%
Other values (19352) 282009
90.1%
2025-03-26T16:19:53.743798image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 311557
 
10.7%
o 246882
 
8.4%
i 226577
 
7.7%
e 220760
 
7.6%
s 205363
 
7.0%
r 186942
 
6.4%
t 155841
 
5.3%
n 142380
 
4.9%
l 139183
 
4.8%
u 122705
 
4.2%
Other values (54) 965732
33.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2923922
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 311557
 
10.7%
o 246882
 
8.4%
i 226577
 
7.7%
e 220760
 
7.6%
s 205363
 
7.0%
r 186942
 
6.4%
t 155841
 
5.3%
n 142380
 
4.9%
l 139183
 
4.8%
u 122705
 
4.2%
Other values (54) 965732
33.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2923922
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 311557
 
10.7%
o 246882
 
8.4%
i 226577
 
7.7%
e 220760
 
7.6%
s 205363
 
7.0%
r 186942
 
6.4%
t 155841
 
5.3%
n 142380
 
4.9%
l 139183
 
4.8%
u 122705
 
4.2%
Other values (54) 965732
33.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2923922
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 311557
 
10.7%
o 246882
 
8.4%
i 226577
 
7.7%
e 220760
 
7.6%
s 205363
 
7.0%
r 186942
 
6.4%
t 155841
 
5.3%
n 142380
 
4.9%
l 139183
 
4.8%
u 122705
 
4.2%
Other values (54) 965732
33.0%

subgenus
Text

Missing 

Distinct293
Distinct (%)12.7%
Missing336575
Missing (%)99.3%
Memory size2.6 MiB
2025-03-26T16:19:53.881522image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length21
Median length16
Mean length10.68685121
Min length3

Characters and Unicode

Total characters24708
Distinct characters48
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)2.0%

Sample

1st rowScapulicambarus
2nd rowAmara
3rd rowAnopheles
4th rowDipremna
5th rowAbax
ValueCountFrequency (%)
ortmannicus 142
 
6.1%
pyrocera 122
 
5.3%
aviticambarus 78
 
3.4%
jugicambarus 68
 
2.9%
creaserinus 64
 
2.8%
pennides 62
 
2.7%
girardiella 56
 
2.4%
scapulicambarus 48
 
2.1%
ochlerotatus 42
 
1.8%
apiocera 38
 
1.6%
Other values (283) 1592
68.9%
2025-03-26T16:19:54.079198image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3126
12.7%
r 2165
 
8.8%
i 1919
 
7.8%
e 1857
 
7.5%
s 1833
 
7.4%
o 1447
 
5.9%
c 1338
 
5.4%
u 1295
 
5.2%
n 1222
 
4.9%
l 1179
 
4.8%
Other values (38) 7327
29.7%

Most occurring categories

ValueCountFrequency (%)
(unknown) 24708
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 3126
12.7%
r 2165
 
8.8%
i 1919
 
7.8%
e 1857
 
7.5%
s 1833
 
7.4%
o 1447
 
5.9%
c 1338
 
5.4%
u 1295
 
5.2%
n 1222
 
4.9%
l 1179
 
4.8%
Other values (38) 7327
29.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 24708
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 3126
12.7%
r 2165
 
8.8%
i 1919
 
7.8%
e 1857
 
7.5%
s 1833
 
7.4%
o 1447
 
5.9%
c 1338
 
5.4%
u 1295
 
5.2%
n 1222
 
4.9%
l 1179
 
4.8%
Other values (38) 7327
29.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 24708
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 3126
12.7%
r 2165
 
8.8%
i 1919
 
7.8%
e 1857
 
7.5%
s 1833
 
7.4%
o 1447
 
5.9%
c 1338
 
5.4%
u 1295
 
5.2%
n 1222
 
4.9%
l 1179
 
4.8%
Other values (38) 7327
29.7%

specificEpithet
Text

Missing 

Distinct23255
Distinct (%)7.6%
Missing33294
Missing (%)9.8%
Memory size2.6 MiB
2025-03-26T16:19:54.230449image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length23
Median length19
Mean length7.933319808
Min length2

Characters and Unicode

Total characters2424367
Distinct characters48
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3389 ?
Unique (%)1.1%

Sample

1st rowfernaldella
2nd rowsp.
3rd rowbolzi
4th rowgranularis
5th rowscopas
ValueCountFrequency (%)
sp 49993
 
16.3%
truncatus 1931
 
0.6%
cinereus 1838
 
0.6%
delphis 1665
 
0.5%
porphyriticus 816
 
0.3%
acutus 780
 
0.3%
opacum 767
 
0.3%
hoffmani 640
 
0.2%
maculatus 635
 
0.2%
nigripes 625
 
0.2%
Other values (23231) 246222
80.5%
2025-03-26T16:19:54.437445image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 298519
12.3%
i 250695
10.3%
s 244744
 
10.1%
e 177381
 
7.3%
r 154624
 
6.4%
l 153692
 
6.3%
u 141592
 
5.8%
n 141520
 
5.8%
t 129381
 
5.3%
p 116730
 
4.8%
Other values (38) 615489
25.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2424367
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 298519
12.3%
i 250695
10.3%
s 244744
 
10.1%
e 177381
 
7.3%
r 154624
 
6.4%
l 153692
 
6.3%
u 141592
 
5.8%
n 141520
 
5.8%
t 129381
 
5.3%
p 116730
 
4.8%
Other values (38) 615489
25.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2424367
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 298519
12.3%
i 250695
10.3%
s 244744
 
10.1%
e 177381
 
7.3%
r 154624
 
6.4%
l 153692
 
6.3%
u 141592
 
5.8%
n 141520
 
5.8%
t 129381
 
5.3%
p 116730
 
4.8%
Other values (38) 615489
25.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2424367
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 298519
12.3%
i 250695
10.3%
s 244744
 
10.1%
e 177381
 
7.3%
r 154624
 
6.4%
l 153692
 
6.3%
u 141592
 
5.8%
n 141520
 
5.8%
t 129381
 
5.3%
p 116730
 
4.8%
Other values (38) 615489
25.4%

infraspecificEpithet
Text

Missing 

Distinct1866
Distinct (%)15.8%
Missing327099
Missing (%)96.5%
Memory size2.6 MiB
2025-03-26T16:19:54.581601image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length20
Median length17
Mean length9.025788938
Min length3

Characters and Unicode

Total characters106396
Distinct characters31
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique738 ?
Unique (%)6.3%

Sample

1st rowcinereus
2nd rowbenjamina
3rd rowmexicana
4th rowdoliatus
5th rowpallidirostris
ValueCountFrequency (%)
pennsylvanicus 616
 
5.2%
cinereus 494
 
4.2%
insignis 268
 
2.3%
talpoides 246
 
2.1%
melas 246
 
2.1%
noveboracensis 196
 
1.7%
dickeyi 167
 
1.4%
dorsalis 125
 
1.1%
cherriei 124
 
1.1%
sacarensis 109
 
0.9%
Other values (1859) 9202
78.0%
2025-03-26T16:19:54.801276image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 12503
11.8%
s 11679
11.0%
a 11282
10.6%
e 9337
8.8%
n 8896
 
8.4%
r 6817
 
6.4%
u 6456
 
6.1%
c 5925
 
5.6%
l 5455
 
5.1%
o 5241
 
4.9%
Other values (21) 22805
21.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 106396
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i 12503
11.8%
s 11679
11.0%
a 11282
10.6%
e 9337
8.8%
n 8896
 
8.4%
r 6817
 
6.4%
u 6456
 
6.1%
c 5925
 
5.6%
l 5455
 
5.1%
o 5241
 
4.9%
Other values (21) 22805
21.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 106396
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i 12503
11.8%
s 11679
11.0%
a 11282
10.6%
e 9337
8.8%
n 8896
 
8.4%
r 6817
 
6.4%
u 6456
 
6.1%
c 5925
 
5.6%
l 5455
 
5.1%
o 5241
 
4.9%
Other values (21) 22805
21.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 106396
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i 12503
11.8%
s 11679
11.0%
a 11282
10.6%
e 9337
8.8%
n 8896
 
8.4%
r 6817
 
6.4%
u 6456
 
6.1%
c 5925
 
5.6%
l 5455
 
5.1%
o 5241
 
4.9%
Other values (21) 22805
21.4%

taxonRank
Text

Missing 

Distinct7
Distinct (%)0.1%
Missing327114
Missing (%)96.5%
Memory size2.6 MiB
2025-03-26T16:19:54.845157image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.757326085
Min length3

Characters and Unicode

Total characters114873
Distinct characters18
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowsubspecies
2nd rowvariety
3rd rowsubspecies
4th rowsubspecies
5th rowsubspecies
ValueCountFrequency (%)
subspecies 10867
92.3%
variety 847
 
7.2%
forma 39
 
0.3%
var 18
 
0.2%
agg 1
 
< 0.1%
fo 1
 
< 0.1%
2025-03-26T16:19:54.932360image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 32601
28.4%
e 22581
19.7%
i 11714
 
10.2%
b 10867
 
9.5%
p 10867
 
9.5%
c 10867
 
9.5%
u 10867
 
9.5%
a 905
 
0.8%
r 904
 
0.8%
t 847
 
0.7%
Other values (8) 1853
 
1.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 114873
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 32601
28.4%
e 22581
19.7%
i 11714
 
10.2%
b 10867
 
9.5%
p 10867
 
9.5%
c 10867
 
9.5%
u 10867
 
9.5%
a 905
 
0.8%
r 904
 
0.8%
t 847
 
0.7%
Other values (8) 1853
 
1.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 114873
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 32601
28.4%
e 22581
19.7%
i 11714
 
10.2%
b 10867
 
9.5%
p 10867
 
9.5%
c 10867
 
9.5%
u 10867
 
9.5%
a 905
 
0.8%
r 904
 
0.8%
t 847
 
0.7%
Other values (8) 1853
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 114873
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 32601
28.4%
e 22581
19.7%
i 11714
 
10.2%
b 10867
 
9.5%
p 10867
 
9.5%
c 10867
 
9.5%
u 10867
 
9.5%
a 905
 
0.8%
r 904
 
0.8%
t 847
 
0.7%
Other values (8) 1853
 
1.6%
Distinct8739
Distinct (%)5.3%
Missing174272
Missing (%)51.4%
Memory size2.6 MiB
2025-03-26T16:19:55.061349image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Length

Max length60
Median length52
Mean length9.057661817
Min length2

Characters and Unicode

Total characters1491027
Distinct characters87
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1934 ?
Unique (%)1.2%

Sample

1st row(Riley)
2nd row(Roding)
3rd rowKrylova & Moskalev
4th rowKearfott
5th row(Leconte)
ValueCountFrequency (%)
18515
 
7.9%
linnaeus 4246
 
1.8%
l 3885
 
1.7%
walker 3710
 
1.6%
barnes 3618
 
1.5%
mcdunnough 3339
 
1.4%
hobbs 3056
 
1.3%
dyar 2660
 
1.1%
busck 2452
 
1.0%
grote 2439
 
1.0%
Other values (4974) 186510
79.6%
2025-03-26T16:19:55.278161image/svg+xmlMatplotlib v3.9.4, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 122376
 
8.2%
a 106263
 
7.1%
r 99340
 
6.7%
n 88307
 
5.9%
69815
 
4.7%
o 67894
 
4.6%
l 64913
 
4.4%
i 63784
 
4.3%
s 62827
 
4.2%
( 55225
 
3.7%
Other values (77) 690283
46.3%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1491027
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 122376
 
8.2%
a 106263
 
7.1%
r 99340
 
6.7%
n 88307
 
5.9%
69815
 
4.7%
o 67894
 
4.6%
l 64913
 
4.4%
i 63784
 
4.3%
s 62827
 
4.2%
( 55225
 
3.7%
Other values (77) 690283
46.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1491027
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 122376
 
8.2%
a 106263
 
7.1%
r 99340
 
6.7%
n 88307
 
5.9%
69815
 
4.7%
o 67894
 
4.6%
l 64913
 
4.4%
i 63784
 
4.3%
s 62827
 
4.2%
( 55225
 
3.7%
Other values (77) 690283
46.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1491027
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 122376
 
8.2%
a 106263
 
7.1%
r 99340
 
6.7%
n 88307
 
5.9%
69815
 
4.7%
o 67894
 
4.6%
l 64913
 
4.4%
i 63784
 
4.3%
s 62827
 
4.2%
( 55225
 
3.7%
Other values (77) 690283
46.3%